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2.e1845539.chunk.js

2.e1845539.chunk.js 1.6 MB
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e=Object(m.a)(b.a.mark((function e(){return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:throw new Error("getWeights() is not implemented for this optimizer yet.");case 1:case"end":return e.stop()}}),e)})));return function(){return e.apply(this,arguments)}}()},{key:"setWeights",value:function(){var e=Object(m.a)(b.a.mark((function e(t){return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:throw new Error("setWeights() is not implemented for this optimizer class "+"".concat(this.getClassName()));case 1:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}()},{key:"extractIterations",value:function(){var e=Object(m.a)(b.a.mark((function e(t){return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,t[0].tensor.data();case 2:return this.iterations_=e.sent[0],e.abrupt("return",t.slice(1));case 4:case"end":return e.stop()}}),e,this)})));return function(t){return 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c=t.accumulatedFirstMoment[i].variable,l=t.accumulatedSecondMoment[i].variable,d=Object(ct.a)(Object(lt.a)(c,t.beta1),Object(lt.a)(s,1-t.beta1)),f=Object(ct.a)(Object(lt.a)(l,t.beta2),Object(lt.a)(Object(ft.a)(s),1-t.beta2)),p=Object(ut.a)(d,r),h=Object(ut.a)(f,a);c.assign(d),l.assign(f);var b=Object(ct.a)(Object(lt.a)(Object(ut.a)(p,Object(ct.a)(Object(dt.a)(h),t.epsilon)),-t.learningRate),o);o.assign(b)}})),t.accBeta1.assign(Object(lt.a)(t.accBeta1,t.beta1)),t.accBeta2.assign(Object(lt.a)(t.accBeta2,t.beta2))})),this.incrementIterations()}},{key:"dispose",value:function(){this.accBeta1.dispose(),this.accBeta2.dispose(),null!=this.accumulatedFirstMoment&&Object(nt.b)(this.accumulatedFirstMoment.map((function(e){return e.variable}))),null!=this.accumulatedSecondMoment&&Object(nt.b)(this.accumulatedSecondMoment.map((function(e){return e.variable})))}},{key:"getWeights",value:function(){var e=Object(m.a)(b.a.mark((function e(){var t;return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return t=[].concat(Object(de.a)(this.accumulatedFirstMoment),Object(de.a)(this.accumulatedSecondMoment)),e.next=3,this.saveIterations();case 3:return e.t0=e.sent,e.abrupt("return",[e.t0].concat(t.map((function(e){return{name:e.originalName,tensor:e.variable}}))));case 5:case"end":return e.stop()}}),e,this)})));return function(){return e.apply(this,arguments)}}()},{key:"setWeights",value:function(){var e=Object(m.a)(b.a.mark((function e(t){var n,r=this;return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this.extractIterations(t);case 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s=Array.isArray(e)?e[i].tensor:e[n];if(null!=s){var c=t.accumulatedFirstMoment[i].variable,l=t.accumulatedWeightedInfNorm[i].variable,d=Object(ct.a)(Object(lt.a)(c,t.beta1),Object(lt.a)(s,1-t.beta1)),f=Object(lt.a)(l,t.beta2),p=Object(Ot.a)(s),h=Object(xt.a)(f,p);c.assign(d),l.assign(h);var b=Object(ct.a)(Object(lt.a)(Object(ut.a)(a,r),Object(ut.a)(d,Object(ct.a)(h,t.epsilon))),o);o.assign(b)}})),t.iteration.assign(Object(ct.a)(t.iteration,1)),t.accBeta1.assign(Object(lt.a)(t.accBeta1,t.beta1))})),this.incrementIterations()}},{key:"dispose",value:function(){this.accBeta1.dispose(),this.iteration.dispose(),null!=this.accumulatedFirstMoment&&Object(nt.b)(this.accumulatedFirstMoment.map((function(e){return e.variable}))),null!=this.accumulatedWeightedInfNorm&&Object(nt.b)(this.accumulatedWeightedInfNorm.map((function(e){return e.variable})))}},{key:"getWeights",value:function(){var e=Object(m.a)(b.a.mark((function e(){return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:throw 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t=this;(Array.isArray(e)?e.map((function(e){return e.name})):Object.keys(e)).forEach((function(n,r){var a=Array.isArray(e)?e[r].tensor:e[n];if(null!=a){var i=u.a.registeredVariables[n];Object(nt.h)((function(){var e=Object(ct.a)(Object(lt.a)(t.c,a),i);i.assign(e)}))}})),this.incrementIterations()}},{key:"setLearningRate",value:function(e){this.learningRate=e,null!=this.c&&this.c.dispose(),this.c=Object(nt.d)(Object(at.a)(-e))}},{key:"dispose",value:function(){this.c.dispose()}},{key:"getWeights",value:function(){var e=Object(m.a)(b.a.mark((function e(){return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this.saveIterations();case 2:return e.t0=e.sent,e.abrupt("return",[e.t0]);case 4:case"end":return e.stop()}}),e,this)})));return function(){return e.apply(this,arguments)}}()},{key:"setWeights",value:function(){var e=Object(m.a)(b.a.mark((function e(t){return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this.extractIterations(t);case 2:if(0===(t=e.sent).length){e.next=5;break}throw new Error("SGD optimizer does not have settable weights.");case 5:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}()},{key:"getConfig",value:function(){return{learningRate:this.learningRate}}}],[{key:"fromConfig",value:function(e,t){return new e(t.learningRate)}}]),n}(it);wt.className="SGD",$e(wt);var jt=function(e){Object(et.a)(n,e);var t=Object(tt.a)(n);function n(e,r){var a,i=arguments.length>2&&void 0!==arguments[2]&&arguments[2];return Object(l.a)(this,n),(a=t.call(this,e)).learningRate=e,a.momentum=r,a.useNesterov=i,a.accumulations=[],a.m=Object(at.a)(a.momentum),a}return Object(d.a)(n,[{key:"applyGradients",value:function(e){var t=this;(Array.isArray(e)?e.map((function(e){return e.name})):Object.keys(e)).forEach((function(n,r){var a=u.a.registeredVariables[n];if(null==t.accumulations[r]){t.accumulations[r]={originalName:"".concat(n,"/momentum"),variable:Object(nt.h)((function(){return Object(pt.a)(a).variable(false)}))}}var i=t.accumulations[r].variable,o=Array.isArray(e)?e[r].tensor:e[n];null!=o&&Object(nt.h)((function(){var e,n=Object(ct.a)(Object(lt.a)(t.m,i),o);e=t.useNesterov?Object(ct.a)(Object(lt.a)(t.c,Object(ct.a)(o,Object(lt.a)(n,t.m))),a):Object(ct.a)(Object(lt.a)(t.c,n),a),i.assign(n),a.assign(e)}))})),this.incrementIterations()}},{key:"dispose",value:function(){this.m.dispose(),null!=this.accumulations&&Object(nt.b)(this.accumulations.map((function(e){return e.variable})))}},{key:"setMomentum",value:function(e){this.momentum=e}},{key:"getWeights",value:function(){var e=Object(m.a)(b.a.mark((function e(){return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this.saveIterations();case 2:return e.t0=e.sent,e.abrupt("return",[e.t0].concat(this.accumulations.map((function(e){return{name:e.originalName,tensor:e.variable}}))));case 4:case"end":return e.stop()}}),e,this)})));return function(){return e.apply(this,arguments)}}()},{key:"setWeights",value:function(){var e=Object(m.a)(b.a.mark((function e(t){return b.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,this.extractIterations(t);case 2:t=e.sent,!1,this.accumulations=t.map((function(e){return{originalName:e.name,variable:e.tensor.variable(false)}}));case 5:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}()},{key:"getConfig",value:function(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}}],[{key:"fromConfig",value:function(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}}]),n}(wt);jt.className="Momentum",$e(jt);var St=function(e){Object(et.a)(n,e);var t=Object(tt.a)(n);function n(e){var 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")+"Reusing existing backend factory."),!1):(this.registryFactory[e]={factory:t,priority:n},!0)}},{key:"setBackend",value:function(){var e=Object(s.a)(o.a.mark((function e(t){var n,r;return o.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(null!=this.registryFactory[t]){e.next=2;break}throw new Error("Backend name '".concat(t,"' not found in registry"));case 2:if(this.backendName=t,null!=this.registry[t]){e.next=16;break}if(this.backendInstance=null,n=this.initializeBackend(t),r=n.success,!n.asyncInit){e.next=12;break}return e.next=9,r;case 9:e.t0=e.sent,e.next=13;break;case 12:e.t0=r;case 13:if(e.t0){e.next=16;break}return e.abrupt("return",!1);case 16:return this.backendInstance=this.registry[t],this.setupRegisteredKernels(),this.profiler=new v(this.backendInstance),e.abrupt("return",!0);case 20:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}()},{key:"setupRegisteredKernels",value:function(){var e=this;Object(h.c)(this.backendName).forEach((function(t){null!=t.setupFunc&&t.setupFunc(e.backendInstance)}))}},{key:"disposeRegisteredKernels",value:function(e){var t=this;Object(h.c)(e).forEach((function(n){null!=n.disposeFunc&&n.disposeFunc(t.registry[e])}))}},{key:"initializeBackend",value:function(e){var t=this,n=this.registryFactory[e];if(null==n)throw new Error("Cannot initialize backend ".concat(e,", no registration found."));try{var r=n.factory();if(!r||r instanceof l.b||"function"!==typeof r.then)return this.registry[e]=r,{success:!0,asyncInit:!1};var a=++this.pendingBackendInitId,i=r.then((function(n){return!(a<t.pendingBackendInitId)&&(t.registry[e]=n,t.pendingBackendInit=null,!0)})).catch((function(n){return a<t.pendingBackendInitId||(t.pendingBackendInit=null,console.warn("Initialization of backend ".concat(e," failed")),console.warn(n.stack||n.message)),!1}));return this.pendingBackendInit=i,{success:i,asyncInit:!0}}catch(o){return console.warn("Initialization of backend ".concat(e," failed")),console.warn(o.stack||o.message),{success:!1,asyncInit:!1}}}},{key:"removeBackend",value:function(e){if(!(e in this.registryFactory))throw new Error("".concat(e," backend not found in registry"));this.backendName===e&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}},{key:"getSortedBackends",value:function(){var e=this;if(0===Object.keys(this.registryFactory).length)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((function(t,n){return e.registryFactory[n].priority-e.registryFactory[t].priority}))}},{key:"initializeBackendsAndReturnBest",value:function(){for(var e=this.getSortedBackends(),t=0;t<e.length;t++){var n=e[t],r=this.initializeBackend(n),a=r.success,i=r.asyncInit;if(i||a)return{name:n,asyncInit:i}}throw new Error("Could not initialize any backends, all backend initializations failed.")}},{key:"moveData",value:function(e,t){var n=this.state.tensorInfo.get(t),r=n.backend,a=this.readSync(t),i=r.refCount(t);r.disposeData(t,!0),n.backend=e,e.move(t,a,n.shape,n.dtype,i),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}},{key:"tidy",value:function(e,t){var n,r=this,a=null;if(null==t){if("function"!==typeof e)throw new Error("Please provide a function to tidy()");t=e}else{if("string"!==typeof e&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if("function"!==typeof t)throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");a=e}return this.scopedRun((function(){return r.startScope(a)}),(function(){return r.endScope(n)}),(function(){return(n=t())instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n}))}},{key:"scopedRun",value:function(e,t,n){e();try{var r=n();return t(),r}catch(a){throw t(),a}}},{key:"nextTensorId",value:function(){return e.nextTensorId++}},{key:"nextVariableId",value:function(){return e.nextVariableId++}},{key:"clone",value:function(e){var t=C.runKernel(p.rb,{x:e}),n={x:e};return this.addTapeNode(this.state.activeScope.name,n,[t],(function(e){return{x:function(){var t={x:e},n={dtype:"float32"};return C.runKernel(p.w,t,n)}}}),[],{}),t}},{key:"runKernel",value:function(e,t,n){if(null==this.backendName&&this.backend,!(null!=Object(h.b)(e,this.backendName)))throw new Error("Kernel '".concat(e,"' not registered for backend '").concat(this.backendName,"'"));return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}},{key:"shouldCheckForMemLeaks",value:function(){return this.ENV.getBool("IS_TEST")}},{key:"checkKernelForMemLeak",value:function(e,t,n){var r=this.backend.numDataIds(),a=0;n.forEach((function(e){a+="complex64"===e.dtype?3:1}));var i=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=r-t-a-i;if(o>0)throw new Error("Backend '".concat(this.backendName,"' has an internal memory leak ")+"(".concat(o," data ids) after running '").concat(e,"'"))}},{key:"runKernelFunc",value:function(e){var t,n,r,a=this,i=[],o=this.isTapeOn(),s=this.state.numBytes,c=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0),null==this.backendName&&this.backend;var u=w(e)?e.kernelName:null!=this.state.activeScope?this.state.activeScope.name:"";if(w(e)){var l=e.kernelName,d=e.inputs,f=e.attrs;null==this.backendName&&this.backend;var p=Object(h.b)(l,this.backendName);m.b(null!=p,(function(){return"Cannot find registered kernel '".concat(l,"' for backend '").concat(a.backendName,"'")})),n=function(){var e=a.backend.numDataIds();r=p.kernelFunc({inputs:d,attrs:f,backend:a.backend});var t=Array.isArray(r)?r:[r];a.shouldCheckForMemLeaks()&&a.checkKernelForMemLeak(l,e,t);var n=t.map((function(e){if(null!=e.rank)return e;var t=e.dataId,n=e.shape,r=e.dtype;return a.makeTensorFromDataId(t,n,r)}));if(o){var s=a.getTensorsForGradient(l,d,n);i=a.saveTensorsForBackwardMode(s)}return n}}else{var b=e.forwardFunc,v=function(e){o&&(i=e.map((function(e){return a.keep(a.clone(e))})))};n=function(){var e=a.backend.numDataIds();r=a.tidy((function(){return b(a.backend,v)}));var t=Array.isArray(r)?r:[r];return a.shouldCheckForMemLeaks()&&a.checkKernelForMemLeak(u,e,t),t}}var g,y=e.inputs,O=e.attrs,x=w(e)?null:e.backwardsFunc;return this.scopedRun((function(){return a.state.kernelDepth++}),(function(){return a.state.kernelDepth--}),(function(){a.ENV.getBool("DEBUG")||a.state.profiling?(g=a.profiler.profileKernel(u,y,(function(){return n()})),a.ENV.getBool("DEBUG")&&a.profiler.logKernelProfile(g),t=g.outputs):t=n()})),o&&this.addTapeNode(u,y,t,x,i,O),this.state.profiling&&this.state.activeProfile.kernels.push({name:u,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-c,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(y).map((function(e){return null!=y[e]?y[e].shape:null})),outputShapes:t.map((function(e){return e.shape})),kernelTimeMs:g.timeMs,extraInfo:g.extraInfo}),Array.isArray(r)?t:t[0]}},{key:"saveTensorsForBackwardMode",value:function(e){var t=this;return e.map((function(e){return t.keep(t.clone(e))}))}},{key:"getTensorsForGradient",value:function(e,t,n){var r=Object(h.a)(e);if(null!=r){var a,i=r.inputsToSave||[],o=r.outputsToSave||[];r.saveAllInputs?(m.b(Array.isArray(t),(function(){return"saveAllInputs is true, expected inputs to be an array."})),a=Object.keys(t).map((function(e){return t[e]}))):a=i.map((function(e){return t[e]}));var s=n.filter((function(e,t){return o[t]}));return a.concat(s)}return[]}},{key:"makeTensor",value:function(e,t,n,r){if(null==e)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;var a=e;"string"===n&&m.z(e[0])&&(a=e.map((function(e){return b.encodeString(e)})));var i=r.write(a,t,n),o=new x.a(t,n,i,this.nextTensorId());if(this.trackTensor(o,r),"string"===n){var s=this.state.tensorInfo.get(i),c=Object(m.f)(a);this.state.numBytes+=c-s.bytes,s.bytes=c}return o}},{key:"makeTensorFromDataId",value:function(e,t,n,r){n=n||"float32";var a=new x.a(t,n,e,this.nextTensorId());return this.trackTensor(a,r),a}},{key:"makeVariable",value:function(e){var t=!(arguments.length>1&&void 0!==arguments[1])||arguments[1],n=arguments.length>2?arguments[2]:void 0,r=arguments.length>3?arguments[3]:void 0;n=n||this.nextVariableId().toString(),null!=r&&r!==e.dtype&&(e=e.cast(r));var a=new x.c(e,t,n,this.nextTensorId());if(null!=this.state.registeredVariables[a.name])throw new Error("Variable with name ".concat(a.name," was already registered"));return this.state.registeredVariables[a.name]=a,this.incRef(a,this.backend),a}},{key:"trackTensor",value:function(e,t){this.state.numTensors++,"string"===e.dtype&&this.state.numStringTensors++;var n=0;"complex64"!==e.dtype&&"string"!==e.dtype&&(n=e.size*m.g(e.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:n})),e instanceof x.c||this.track(e)}},{key:"incRef",value:function(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}},{key:"removeDataId",value:function(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}},{key:"disposeTensor",value:function(e){if(this.state.tensorInfo.has(e.dataId)){var t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,"string"===e.dtype&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),"complex64"!==e.dtype&&"string"!==e.dtype){var n=e.size*m.g(e.dtype);this.state.numBytes-=n}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}}},{key:"disposeVariables",value:function(){for(var e in this.state.registeredVariables){var t=this.state.registeredVariables[e];this.disposeVariable(t)}}},{key:"disposeVariable",value:function(e){this.disposeTensor(e),null!=this.state.registeredVariables[e.name]&&delete this.state.registeredVariables[e.name]}},{key:"memory",value:function(){var e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,null==e.reasons&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}},{key:"profile",value:function(){var e=Object(s.a)(o.a.mark((function e(t){var n,i,s,c,u;return o.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return this.state.profiling=!0,n=this.state.numBytes,i=this.state.numTensors,this.state.activeProfile.kernels=[],e.next=6,t();case 6:this.state.activeProfile.result=e.sent,this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max.apply(Math,Object(a.a)(this.state.activeProfile.kernels.map((function(e){return e.totalBytesSnapshot})))),this.state.activeProfile.newBytes=this.state.numBytes-n,this.state.activeProfile.newTensors=this.state.numTensors-i,s=Object(r.a)(this.state.activeProfile.kernels),e.prev=12,s.s();case 14:if((c=s.n()).done){e.next=24;break}return u=c.value,e.next=18,u.kernelTimeMs;case 18:return u.kernelTimeMs=e.sent,e.next=21,u.extraInfo;case 21:u.extraInfo=e.sent;case 22:e.next=14;break;case 24:e.next=29;break;case 26:e.prev=26,e.t0=e.catch(12),s.e(e.t0);case 29:return e.prev=29,s.f(),e.finish(29);case 32:return e.abrupt("return",this.state.activeProfile);case 33:case"end":return e.stop()}}),e,this,[[12,26,29,32]])})));return function(t){return e.apply(this,arguments)}}()},{key:"isTapeOn",value:function(){return this.state.gradientDepth>0&&0===this.state.kernelDepth}},{key:"addTapeNode",value:function(e,t,n,r,a,i){var o=this,s={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:a},c=Object(h.a)(e);null!=c&&(r=c.gradFunc),null!=r&&(s.gradient=function(e){return e=e.map((function(e,t){if(null==e){var r=n[t],a=m.F(r.size,r.dtype);return o.makeTensor(a,r.shape,r.dtype)}return e})),r(e.length>1?e:e[0],a,i)}),this.state.activeTape.push(s)}},{key:"keep",value:function(e){return e.kept=!0,e}},{key:"startTape",value:function(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++}},{key:"endTape",value:function(){this.state.gradientDepth--}},{key:"startScope",value:function(e){var t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}},{key:"endScope",value:function(e){for(var t=this,n=Object(k.getTensorsInContainer)(e),r=new Set(n.map((function(e){return e.id}))),a=0;a<this.state.activeScope.track.length;a++){var i=this.state.activeScope.track[a];i.kept||r.has(i.id)||i.dispose()}var o=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],n.forEach((function(e){e.kept||e.scopeId!==o.id||t.track(e)}))}},{key:"gradients",value:function(e,t,n){var a=this,i=arguments.length>3&&void 0!==arguments[3]&&arguments[3];if(m.b(t.length>0,(function(){return"gradients() received an empty list of xs."})),null!=n&&"float32"!==n.dtype)throw new Error("dy must have 'float32' dtype, but has '".concat(n.dtype,"'"));var o=this.scopedRun((function(){return a.startTape()}),(function(){return a.endTape()}),(function(){return a.tidy("forward",e)}));m.b(o instanceof x.a,(function(){return"The result y returned by f() must be a tensor."}));var s=y(this.state.activeTape,t,o);if(!i&&0===s.length&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",(function(){var e={};e[o.id]=null==n?N(o.shape):n,O(e,s,(function(e){return a.tidy(e)}),T);var i=t.map((function(t){return e[t.id]}));return 0===a.state.gradientDepth&&(a.state.activeTape.forEach((function(e){var t,n=Object(r.a)(e.saved);try{for(n.s();!(t=n.n()).done;){t.value.dispose()}}catch(a){n.e(a)}finally{n.f()}})),a.state.activeTape=null),{value:o,grads:i}}))}},{key:"customGrad",value:function(e){var t=this;return m.b(m.u(e),(function(){return"The f passed in customGrad(f) must be a function."})),function(){for(var n=arguments.length,r=new Array(n),a=0;a<n;a++)r[a]=arguments[a];var i;m.b(r.every((function(e){return e instanceof x.a})),(function(){return"The args passed in customGrad(f)(x1, x2,...) must all be tensors"}));var o={};r.forEach((function(e,t){o[t]=e}));var s=function(t,n){return i=e.apply(void 0,[].concat(r,[n])),m.b(i.value instanceof x.a,(function(){return"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"})),m.b(m.u(i.gradFunc),(function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."})),i.value},c=function(e,t){var n=i.gradFunc(e,t),a=Array.isArray(n)?n:[n];m.b(a.length===r.length,(function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."})),m.b(a.every((function(e){return e instanceof x.a})),(function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors."}));var o={};return a.forEach((function(e,t){o[t]=function(){return e}})),o};return t.runKernelFunc({forwardFunc:s,backwardsFunc:c,inputs:o})}}},{key:"readSync",value:function(e){return this.state.tensorInfo.get(e).backend.readSync(e)}},{key:"read",value:function(e){return this.state.tensorInfo.get(e).backend.read(e)}},{key:"time",value:function(){var e=Object(s.a)(o.a.mark((function e(t){var n,r;return o.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return n=Object(b.now)(),e.next=3,this.backend.time(t);case 3:return(r=e.sent).wallMs=Object(b.now)()-n,e.abrupt("return",r);case 6:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}()},{key:"track",value:function(e){return null!=this.state.activeScope&&(e.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(e)),e}},{key:"registeredVariables",get:function(){return this.state.registeredVariables}},{key:"reset",value:function(){for(var e in this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new j,this.registry)this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete 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hr=Object(j.b)({cropAndResize_:function(e,t,n,r){var a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:"bilinear",i=arguments.length>5&&void 0!==arguments[5]?arguments[5]:0,o=Object(O.a)(e,"image","cropAndResize"),s=Object(O.a)(t,"boxes","cropAndResize","float32"),c=Object(O.a)(n,"boxInd","cropAndResize","int32"),u=s.shape[0];A.b(4===o.rank,(function(){return"Error in cropAndResize: image must be rank 4,"+"but got rank ".concat(o.rank,".")})),A.b(2===s.rank&&4===s.shape[1],(function(){return"Error in cropAndResize: boxes must be have size [".concat(u,",4] ")+"but had shape ".concat(s.shape,".")})),A.b(1===c.rank&&c.shape[0]===u,(function(){return"Error in cropAndResize: boxInd must be have size [".concat(u,"] ")+"but had shape ".concat(s.shape,".")})),A.b(2===r.length,(function(){return"Error in cropAndResize: cropSize must be of length 2, but got "+"length ".concat(r.length,".")})),A.b(r[0]>=1&&r[1]>=1,(function(){return"cropSize must be atleast [1,1], but was 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vr(e,t,n,r,a,i){null==r&&(r=.5),null==a&&(a=Number.NEGATIVE_INFINITY),null==i&&(i=0);var o=e.shape[0];return n=Math.min(n,o),A.b(0<=r&&r<=1,(function(){return"iouThreshold must be in [0, 1], but was '".concat(r,"'")})),A.b(2===e.rank,(function(){return"boxes must be a 2D tensor, but was of rank '".concat(e.rank,"'")})),A.b(4===e.shape[1],(function(){return"boxes must have 4 columns, but 2nd dimension was ".concat(e.shape[1])})),A.b(1===t.rank,(function(){return"scores must be a 1D tensor"})),A.b(t.shape[0]===o,(function(){return"scores has incompatible shape with boxes. 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l=e.sent,d=l[0],f=l[1],p=Object(yr.c)(d,f,r,a,i,o),h=p.selectedIndices,b=p.selectedScores,s!==t&&s.dispose(),c!==n&&c.dispose(),e.abrupt("return",{selectedIndices:Object(gn.a)(h,"int32"),selectedScores:Object(gn.a)(b)});case 19:case"end":return e.stop()}}),e)})))).apply(this,arguments)}var jr=function(e,t,n){return wr.apply(this,arguments)};var Sr=Object(j.b)({nonMaxSuppressionPadded_:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:.5,a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:Number.NEGATIVE_INFINITY,i=arguments.length>5&&void 0!==arguments[5]&&arguments[5],o=Object(O.a)(e,"boxes","nonMaxSuppression"),s=Object(O.a)(t,"scores","nonMaxSuppression"),c=vr(o,s,n,r,a,null),u=c.maxOutputSize,l=c.iouThreshold,d=c.scoreThreshold,f={boxes:o,scores:s},p={maxOutputSize:u,iouThreshold:l,scoreThreshold:d,padToMaxOutputSize:i},h=ie.a.runKernel(oe.Yb,f,p);return{selectedIndices:h[0],validOutputs:h[1]}}});function 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n,r,a,i,o,c,u=Object(gn.a)([-1]),l=Object(gn.a)([0]),d=Object(gn.a)([0]),f=0;f<e.size-1;f++){n=Object(N.a)(e,0,f+1),r=Object(N.a)(e,f+1),o=Object(ue.a)(Object(bn.a)(n),t),c=Object(ue.a)(Object(bn.a)(r),t);var p=Object(bn.a)(Object(w.a)(n,Object(At.a)(0,n.size)));a=Object(ue.a)(p,Object(bn.a)(n));var h=Object(ke.a)(r.shape,n.size),b=Object(s.a)(Object(At.a)(0,r.size),h),m=Object(w.a)(r,b);i=Object(ue.a)(Object(bn.a)(m),Object(bn.a)(r));var v=Object(st.a)(a,i),g=Object(st.a)(a,i),y=Object(w.a)(o,c);d=Object(w.a)(Object(w.a)(y,v),g);var O=Object(Ne.a)(d,l);l=Object(An.a)(O,d,l),u=Object(An.a)(O,Object(gn.a)([f]),u)}return u}var Ar=Object(j.b)({threshold_:function(e){var t,n,r,a,i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"binary",o=arguments.length>2&&void 0!==arguments[2]&&arguments[2],c=arguments.length>3&&void 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k=o?Object(De.a)(a,h):Object(Ne.a)(a,h),j=Object(L.a)(Object(w.a)(k,255),"int32");return j}});var Rr=Object(j.b)({transform_:function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:"nearest",r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:"constant",a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:0,i=arguments.length>5?arguments[5]:void 0,o=Object(O.a)(e,"image","transform","float32"),s=Object(O.a)(t,"transforms","transform","float32");A.b(4===o.rank,(function(){return"Error in transform: image must be rank 4,"+"but got rank ".concat(o.rank,".")})),A.b(2===s.rank&&(s.shape[0]===o.shape[0]||1===s.shape[0])&&8===s.shape[1],(function(){return"Error in transform: Input transform should be batch x 8 or 1 x 8"})),A.b(null==i||2===i.length,(function(){return"Error in transform: outputShape must be [height, width] or null, "+"but got ".concat(i,".")}));var c={image:o,transforms:s},u={interpolation:n,fillMode:r,fillValue:a,outputShape:i};return ie.a.runKernel(oe.cd,c,u)}});var Fr=Object(j.b)({bandPart_:function(e,t,n){Object(A.b)(t%1===0,(function(){return"bandPart(): numLower must be an integer, got ".concat(t,".")})),Object(A.b)(n%1===0,(function(){return"bandPart(): numUpper must be an integer, got ".concat(n,".")}));var r=Object(O.a)(e,"a","bandPart");Object(A.b)(r.rank>=2,(function(){return"bandPart(): Rank must be at least 2, got ".concat(r.rank,".")}));var a=r.shape,i=r.shape.slice(-2),o=Object(Zn.a)(i,2),s=o[0],c=o[1];if(!(t<=s))throw new Error("bandPart(): numLower (".concat(t,")")+" must not be greater than the number of rows (".concat(s,")."));if(!(n<=c))throw new Error("bandPart(): numUpper (".concat(n,")")+" must not be greater than the number of columns (".concat(c,")."));t<0&&(t=s),n<0&&(n=c);var u=Object(ye.a)(Object(At.a)(0,s,1,"int32"),[-1,1]),l=Object(At.a)(0,c,1,"int32"),d=Object(st.a)(u,l),f=Object(Ue.a)(Object(De.a)(d,Object(Vt.a)(+t,"int32")),Object(Ie.a)(d,Object(Vt.a)(-n,"int32"))),p=Object(Fn.a)([s,c],r.dtype);return Object(ye.a)(Object(fn.a)(Object(Tn.a)(Object(ye.a)(r,[-1,s,c])).map((function(e){return Object(An.a)(f,e,p)}))),a)}});var Dr=Object(j.b)({gramSchmidt_:function(e){var t;Array.isArray(e)?function(){t=!1,Object(A.b)(null!=e&&e.length>0,(function(){return"Gram-Schmidt process: input must not be null, undefined, or empty"}));for(var n=e[0].shape[0],r=function(t){Object(A.b)(e[t].shape[0]===n,(function(){return"Gram-Schmidt: Non-unique lengths found in the input vectors: "+"(".concat(e[t].shape[0]," vs. ").concat(n,")")}))},a=1;a<e.length;++a)r(a)}():(t=!0,e=Object(cn.a)(e,e.shape[0],0).map((function(e){return Object(dn.a)(e,[0])}))),Object(A.b)(e.length<=e[0].shape[0],(function(){return"Gram-Schmidt: Number of vectors (".concat(e.length,") exceeds 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t=Object(N.a)(i,[e,e],[n-e,1]),c=Object(Wn.a)(t),u=Object(N.a)(i,[e,e],[1,1]),l=Object(An.a)(Object(Ne.a)(u,0),On([[-1]]),On([[1]])),d=Object(st.a)(u,Object(w.a)(l,c)),f=Object(ue.a)(t,d);s=1===f.shape[0]?Object(W.a)(o):Object(x.a)([o,Object(N.a)(f,[1,0],[f.shape[0]-1,f.shape[1]])],0);var p=Object(dt.a)(Object(ue.a)(Object(k.a)(l,d),c)),h=Object(N.a)(i,[e,0],[n-e,r]),b=Object(w.a)(p,s),m=Object(Bn.a)(s);if(0===e)i=Object(st.a)(h,Object(k.a)(b,Object(k.a)(m,h)));else{var v=Object(st.a)(h,Object(k.a)(b,Object(k.a)(m,h)));i=Object(x.a)([Object(N.a)(i,[0,0],[e,r]),v],0)}var g=Object(Bn.a)(b),y=Object(N.a)(a,[0,e],[n,a.shape[1]-e]);if(0===e)a=Object(st.a)(y,Object(k.a)(Object(k.a)(y,s),g));else{var O=Object(st.a)(y,Object(k.a)(Object(k.a)(y,s),g));a=Object(x.a)([Object(N.a)(a,[0,0],[n,e]),O],1)}return[s,i,a]})),d=Object(Zn.a)(l,3);s=d[0],i=d[1],a=d[2],Object(_r.b)([t,c,u])},l=0;l<c;++l)u(l);return!t&&n>r&&(a=Object(N.a)(a,[0,0],[n,r]),i=Object(N.a)(i,[0,0],[r,r])),[a,i]}))}var zr=Object(j.b)({qr_:function(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1];if(Object(A.b)(e.rank>=2,(function(){return"qr() requires input tensor to have a rank >= 2, but got rank ".concat(e.rank)})),2===e.rank)return Mr(e,t);var n=e.shape.slice(0,e.shape.length-2).reduce((function(e,t){return e*t})),r=Object(Tn.a)(Object(ye.a)(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),a=[],i=[];r.forEach((function(e){var n=Mr(e,t),r=Object(Zn.a)(n,2),o=r[0],s=r[1];a.push(o),i.push(s)}));var o=Object(ye.a)(Object(fn.a)(a,0),e.shape),s=Object(ye.a)(Object(fn.a)(i,0),e.shape);return[o,s]}}),Lr=n(56);var Pr=Object(j.b)({computeWeightedLoss_:function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:Lr.a.SUM_BY_NONZERO_WEIGHTS,r=Object(O.a)(e,"losses","computeWeightedLoss"),a=null;null!=t&&(a=Object(O.a)(t,"weights","computeWeightedLoss"));var i=null==a?r:Object(w.a)(r,a);if(n===Lr.a.NONE)return i;if(n===Lr.a.SUM)return Object(bn.a)(i);if(n===Lr.a.MEAN){if(null==a)return Object(Qe.a)(i);var o=r.size/a.size,s=Object(ue.a)(Object(bn.a)(i),Object(bn.a)(a));return o>1?Object(ue.a)(s,Object(Vt.a)(o)):s}if(n===Lr.a.SUM_BY_NONZERO_WEIGHTS){if(null==a)return Object(ue.a)(Object(bn.a)(i),Object(Vt.a)(r.size));var c=Object(w.a)(a,Object(Ze.a)(r.shape)),u=Object(L.a)(Object(bn.a)(Object(ft.a)(c,Object(Vt.a)(0))),"float32");return Object(ue.a)(Object(bn.a)(i),u)}throw Error("Unknown reduction: ".concat(n))}});var Br=Object(j.b)({absoluteDifference_:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:Lr.a.SUM_BY_NONZERO_WEIGHTS,i=Object(O.a)(e,"labels","absoluteDifference"),o=Object(O.a)(t,"predictions","absoluteDifference"),s=null;null!=n&&(s=Object(O.a)(n,"weights","absoluteDifference")),Object(A.e)(i.shape,o.shape,"Error in absoluteDifference: ");var c=Object(a.a)(Object(st.a)(i,o));return Pr(c,s,r)}});var Wr=Object(j.b)({cosineDistance_:function(e,t,n,r){var a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:Lr.a.SUM_BY_NONZERO_WEIGHTS,i=Object(O.a)(e,"labels","cosineDistance"),o=Object(O.a)(t,"predictions","cosineDistance"),s=null;null!=r&&(s=Object(O.a)(r,"weights","cosineDistance")),Object(A.e)(i.shape,o.shape,"Error in cosineDistance: ");var c=Object(Vt.a)(1),u=Object(st.a)(c,Object(bn.a)(Object(w.a)(i,o),n,!0));return Pr(u,s,a)}});var Ur=Object(j.b)({hingeLoss_:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:Lr.a.SUM_BY_NONZERO_WEIGHTS,a=Object(O.a)(e,"labels","hingeLoss"),i=Object(O.a)(t,"predictions","hingeLoss"),o=null;null!=n&&(o=Object(O.a)(n,"weights","hingeLoss")),Object(A.e)(a.shape,i.shape,"Error in hingeLoss: ");var s=Object(Vt.a)(1);a=Object(st.a)(Object(w.a)(Object(Vt.a)(2),a),s);var c=Object(Dt.a)(Object(st.a)(s,Object(w.a)(a,i)));return Pr(c,o,r)}});var Vr=Object(j.b)({huberLoss_:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:1,i=arguments.length>4&&void 0!==arguments[4]?arguments[4]:Lr.a.SUM_BY_NONZERO_WEIGHTS,o=Object(O.a)(e,"labels","huberLoss"),c=Object(O.a)(t,"predictions","huberLoss"),u=null;null!=n&&(u=Object(O.a)(n,"weights","huberLoss")),Object(A.e)(o.shape,c.shape,"Error in huberLoss: ");var l=Object(Vt.a)(r),d=Object(a.a)(Object(st.a)(c,o)),f=Object(nt.a)(d,l),p=Object(st.a)(d,f),h=Object(s.a)(Object(w.a)(Object(Vt.a)(.5),Object(ot.a)(f)),Object(w.a)(l,p));return Pr(h,u,i)}});var Hr=Object(j.b)({logLoss_:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:1e-7,a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:Lr.a.SUM_BY_NONZERO_WEIGHTS,i=Object(O.a)(e,"labels","logLoss"),o=Object(O.a)(t,"predictions","logLoss"),c=null;null!=n&&(c=Object(O.a)(n,"weights","logLoss")),Object(A.e)(i.shape,o.shape,"Error in logLoss: ");var u=Object(Vt.a)(1),l=Object(Vt.a)(r),d=Object(dt.a)(Object(w.a)(i,Object(ze.a)(Object(s.a)(o,l)))),f=Object(w.a)(Object(st.a)(u,i),Object(ze.a)(Object(s.a)(Object(st.a)(u,o),l))),p=Object(st.a)(d,f);return Pr(p,c,a)}});var Gr=Object(j.b)({meanSquaredError_:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:Lr.a.SUM_BY_NONZERO_WEIGHTS,a=Object(O.a)(e,"labels","meanSquaredError"),i=Object(O.a)(t,"predictions","meanSquaredError"),o=null;null!=n&&(o=Object(O.a)(n,"weights","meanSquaredError")),Object(A.e)(a.shape,i.shape,"Error in meanSquaredError: ");var s=Object(ln.a)(a,i);return Pr(s,o,r)}});function qr(e,t){var n=Object(O.a)(e,"labels","sigmoidCrossEntropyWithLogits"),r=Object(O.a)(t,"logits","sigmoidCrossEntropyWithLogits");Object(A.e)(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");var i=Object(Dt.a)(r),o=Object(w.a)(r,n),c=Object(Le.a)(Object(me.a)(Object(dt.a)(Object(a.a)(r))));return Object(s.a)(Object(st.a)(i,o),c)}var Kr=Object(j.b)({sigmoidCrossEntropy_:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:0,a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:Lr.a.SUM_BY_NONZERO_WEIGHTS,i=Object(O.a)(e,"multiClassLabels","sigmoidCrossEntropy"),o=Object(O.a)(t,"logits","sigmoidCrossEntropy"),c=null;if(null!=n&&(c=Object(O.a)(n,"weights","sigmoidCrossEntropy")),Object(A.e)(i.shape,o.shape,"Error in sigmoidCrossEntropy: "),r>0){var u=Object(Vt.a)(r),l=Object(Vt.a)(1),d=Object(Vt.a)(.5);i=Object(s.a)(Object(w.a)(i,Object(st.a)(l,u)),Object(w.a)(d,u))}var f=qr(i,o);return Pr(f,c,a)}});function Xr(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:-1;if(-1===n&&(n=t.rank-1),n!==t.rank-1)throw Error("Softmax cross entropy along a non-last dimension is not yet "+"supported. Labels / logits was rank ".concat(t.rank," ")+"and dim was ".concat(n));var r=Object(Jn.a)((function(e,t,r){var a=Object(We.a)(t,[n],!0),i=Object(st.a)(Object(L.a)(t,"float32"),a);r([e,i]);var o=Object(dt.a)(Object(w.a)(i,e));return{value:Object(bn.a)(o,[n]),gradFunc:function(e,t){var r=Object(Zn.a)(t,2),a=r[0],i=r[1],o=Object(it.e)(e.shape,[n]);return[Object(w.a)(Object(ye.a)(e,o),Object(st.a)(Object(L.a)(a,"float32"),Object(me.a)(i))),Object(w.a)(Object(ye.a)(e,o),Object(st.a)(Object(me.a)(i),Object(L.a)(a,"float32")))]}}}));return r(e,t)}var Yr=Object(j.b)({softmaxCrossEntropy_:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:0,a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:Lr.a.SUM_BY_NONZERO_WEIGHTS,i=Object(O.a)(e,"onehotLabels","softmaxCrossEntropy"),o=Object(O.a)(t,"logits","softmaxCrossEntropy"),c=null;if(null!=n&&(c=Object(O.a)(n,"weights","softmaxCrossEntropy")),Object(A.e)(i.shape,o.shape,"Error in softmaxCrossEntropy: "),r>0){var u=Object(Vt.a)(r),l=Object(Vt.a)(1),d=Object(Vt.a)(i.shape[1]);i=Object(s.a)(Object(w.a)(i,Object(st.a)(l,u)),Object(ue.a)(u,d))}var f=Xr(i,o);return Pr(f,c,a)}});var $r=Object(j.b)({sparseFillEmptyRows_:function(e,t,n,r){var a=Object(O.a)(e,"indices","sparseFillEmptyRows"),i=Object(O.a)(t,"values","sparseFillEmptyRows"),o=Object(O.a)(n,"denseShape","sparseFillEmptyRows"),s=Object(O.a)(r,"defaultValue","sparseFillEmptyRows",i.dtype);if(2!==a.rank)throw new Error("Indices should be Tensor2D but received shape\n        ".concat(a.shape));if(1!==i.rank)throw new Error("Values should be Tensor1D but received shape ".concat(i.shape));if(1!==o.rank)throw new Error("Dense shape should be Tensor1D but received shape ".concat(o.shape));if(0!==s.rank)throw new Error("Default value should be a scalar but received shape ".concat(s.shape));var 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this.throwIfDisposed(),Object(Sn.a)(this)};var In=n(249);Object(Nn.d)().prototype.acos=function(){return this.throwIfDisposed(),Object(In.a)(this)};var Cn=n(250);Object(Nn.d)().prototype.acosh=function(){return this.throwIfDisposed(),Object(Cn.a)(this)},Object(Nn.d)().prototype.add=function(e){return this.throwIfDisposed(),Object(T.a)(this,e)};var Tn=n(190);Object(Nn.d)().prototype.all=function(e,t){return this.throwIfDisposed(),Object(Tn.a)(this,e,t)};var En=n(191);Object(Nn.d)().prototype.any=function(e,t){return this.throwIfDisposed(),Object(En.a)(this,e,t)};var An=n(192);Object(Nn.d)().prototype.argMax=function(e){return this.throwIfDisposed(),Object(An.a)(this,e)};var Rn=n(193);Object(Nn.d)().prototype.argMin=function(e){return this.throwIfDisposed(),Object(Rn.a)(this,e)},Object(Nn.d)().prototype.asScalar=function(){return this.throwIfDisposed(),Object(M.b)(1===this.size,(function(){return"The array must have only 1 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this.throwIfDisposed(),Object(Un.a)(this,e,t)};var Vn=n(21);Object(Nn.d)().prototype.concat=function(e,t){return this.throwIfDisposed(),e instanceof Nn.a&&(e=[e]),Object(tn.a)([this].concat(Object(Vn.a)(e)),t)};var Hn=n(196);Object(Nn.d)().prototype.conv1d=function(e,t,n,r,a,i){return this.throwIfDisposed(),Object(Hn.a)(this,e,t,n,r,a,i)};var Gn=n(197);Object(Nn.d)().prototype.conv2dTranspose=function(e,t,n,r,a){return this.throwIfDisposed(),Object(Gn.a)(this,e,t,n,r,a)},Object(Nn.d)().prototype.conv2d=function(e,t,n,r,a,i){return this.throwIfDisposed(),Object(se.a)(this,e,t,n,r,a,i)},Object(Nn.d)().prototype.cos=function(){return this.throwIfDisposed(),Object(Vt.a)(this)},Object(Nn.d)().prototype.cosh=function(){return this.throwIfDisposed(),Object(Gt.a)(this)},Object(Nn.d)().prototype.cumsum=function(e,t,n){return this.throwIfDisposed(),Object(ve.a)(this,e,t,n)};var qn=n(199);Object(Nn.d)().prototype.depthToSpace=function(e,t){return this.throwIfDisposed(),Object(qn.a)(this,e,t)};var Kn=n(116);Object(Nn.d)().prototype.depthwiseConv2d=function(e,t,n,r,a,i){return this.throwIfDisposed(),Object(Kn.a)(this,e,t,n,r,a,i)};var Xn=n(200);Object(Nn.d)().prototype.dilation2d=function(e,t,n,r,a){return this.throwIfDisposed(),Object(Xn.a)(this,e,t,n,r,a)};var Yn=n(201);Object(Nn.d)().prototype.divNoNan=function(e){return this.throwIfDisposed(),Object(Yn.a)(this,e)},Object(Nn.d)().prototype.div=function(e){return this.throwIfDisposed(),Object(f.a)(this,e)};var $n=n(202);Object(Nn.d)().prototype.dot=function(e){return this.throwIfDisposed(),Object($n.a)(this,e)};var Qn=n(147);Object(Nn.d)().prototype.elu=function(){return this.throwIfDisposed(),Object(Qn.a)(this)},Object(Nn.d)().prototype.equal=function(e){return this.throwIfDisposed(),Object(Qe.a)(this,e)};var Zn=n(262);Object(Nn.d)().prototype.erf=function(){return this.throwIfDisposed(),Object(Zn.a)(this)},Object(Nn.d)().prototype.exp=function(){return this.throwIfDisposed(),Object(Se.a)(this)},Object(Nn.d)().prototype.expandDims=function(e){return this.throwIfDisposed(),Object(mn.a)(this,e)};var Jn=n(263);Object(Nn.d)().prototype.expm1=function(){return this.throwIfDisposed(),Object(Jn.a)(this)};var er=n(159);Object(Nn.d)().prototype.fft=function(){return this.throwIfDisposed(),Object(er.a)(this)},Object(Nn.d)().prototype.flatten=function(){return this.throwIfDisposed(),Object(x.a)(this,[this.size])},Object(Nn.d)().prototype.floor=function(){return this.throwIfDisposed(),Object(ft.a)(this)};var tr=n(146);Object(Nn.d)().prototype.floorDiv=function(e){return this.throwIfDisposed(),Object(tr.a)(this,e)},Object(Nn.d)().prototype.gather=function(e,t){return this.throwIfDisposed(),Object(vn.a)(this,e,t)},Object(Nn.d)().prototype.greaterEqual=function(e){return this.throwIfDisposed(),Object(Y.a)(this,e)},Object(Nn.d)().prototype.greater=function(e){return this.throwIfDisposed(),Object(He.a)(this,e)};var nr=n(134);Object(Nn.d)().prototype.ifft=function(){return this.throwIfDisposed(),Object(nr.a)(this)};var rr=n(219);Object(Nn.d)().prototype.irfft=function(){return this.throwIfDisposed(),Object(rr.a)(this)};var ar=n(264);Object(Nn.d)().prototype.isFinite=function(){return this.throwIfDisposed(),Object(ar.a)(this)};var ir=n(265);Object(Nn.d)().prototype.isInf=function(){return this.throwIfDisposed(),Object(ir.a)(this)};var or=n(266);Object(Nn.d)().prototype.isNaN=function(){return this.throwIfDisposed(),Object(or.a)(this)};var sr=n(150);Object(Nn.d)().prototype.leakyRelu=function(e){return this.throwIfDisposed(),Object(sr.a)(this,e)},Object(Nn.d)().prototype.lessEqual=function(e){return this.throwIfDisposed(),Object($.a)(this,e)},Object(Nn.d)().prototype.less=function(e){return this.throwIfDisposed(),Object(et.a)(this,e)};var cr=n(203);Object(Nn.d)().prototype.localResponseNormalization=function(e,t,n,r){return this.throwIfDisposed(),Object(cr.a)(this,e,t,n,r)};var ur=n(268);Object(Nn.d)().prototype.logSigmoid=function(){return this.throwIfDisposed(),Object(ur.a)(this)};var lr=n(269);Object(Nn.d)().prototype.logSoftmax=function(e){return this.throwIfDisposed(),Object(lr.a)(this,e)};var dr=n(152);Object(Nn.d)().prototype.logSumExp=function(e,t){return this.throwIfDisposed(),Object(dr.a)(this,e,t)},Object(Nn.d)().prototype.log=function(){return this.throwIfDisposed(),Object(kt.a)(this)};var fr=n(204);Object(Nn.d)().prototype.log1p=function(){return this.throwIfDisposed(),Object(fr.a)(this)},Object(Nn.d)().prototype.logicalAnd=function(e){return this.throwIfDisposed(),Object(Q.a)(this,e)},Object(Nn.d)().prototype.logicalNot=function(){return this.throwIfDisposed(),Object(zt.a)(this)};var pr=n(153);Object(Nn.d)().prototype.logicalOr=function(e){return this.throwIfDisposed(),Object(pr.a)(this,e)};var hr=n(206);Object(Nn.d)().prototype.logicalXor=function(e){return this.throwIfDisposed(),Object(hr.a)(this,e)},Object(Nn.d)().prototype.matMul=function(e,t,n){return this.throwIfDisposed(),Object(U.a)(this,e,t,n)};var br=n(154);Object(Nn.d)().prototype.maxPool=function(e,t,n,r){return this.throwIfDisposed(),Object(br.a)(this,e,t,n,r)};var mr=n(94);Object(Nn.d)().prototype.max=function(e,t){return this.throwIfDisposed(),Object(mr.a)(this,e,t)},Object(Nn.d)().prototype.maximum=function(e){return this.throwIfDisposed(),Object(gn.a)(this,e)};var vr=n(112);Object(Nn.d)().prototype.mean=function(e,t){return this.throwIfDisposed(),Object(vr.a)(this,e,t)};var gr=n(132);Object(Nn.d)().prototype.min=function(e,t){return this.throwIfDisposed(),Object(gr.a)(this,e,t)};var yr=n(155);Object(Nn.d)().prototype.minimum=function(e){return this.throwIfDisposed(),Object(yr.a)(this,e)};var Or=n(207);Object(Nn.d)().prototype.mirrorPad=function(e,t){return this.throwIfDisposed(),Object(Or.a)(this,e,t)};var xr=n(208);Object(Nn.d)().prototype.mod=function(e){return this.throwIfDisposed(),Object(xr.a)(this,e)},Object(Nn.d)().prototype.mul=function(e){return this.throwIfDisposed(),Object(u.a)(this,e)},Object(Nn.d)().prototype.neg=function(){return this.throwIfDisposed(),Object(p.a)(this)};var kr=n(163);Object(Nn.d)().prototype.norm=function(e,t,n){return this.throwIfDisposed(),Object(kr.a)(this,e,t,n)};var wr=n(156);Object(Nn.d)().prototype.notEqual=function(e){return this.throwIfDisposed(),Object(wr.a)(this,e)};var jr=n(209);Object(Nn.d)().prototype.oneHot=function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:0;return this.throwIfDisposed(),Object(jr.a)(this,e,t,n)};var Sr=n(273);Object(Nn.d)().prototype.onesLike=function(){return this.throwIfDisposed(),Object(Sr.a)(this)},Object(Nn.d)().prototype.pad=function(e,t){return this.throwIfDisposed(),Object(Kt.a)(this,e,t)};var Nr=n(210);Object(Nn.d)().prototype.pool=function(e,t,n,r,a){return this.throwIfDisposed(),Object(Nr.a)(this,e,t,n,r,a)},Object(Nn.d)().prototype.pow=function(e){return this.throwIfDisposed(),Object(wt.a)(this,e)};var Ir=n(157);Object(Nn.d)().prototype.prelu=function(e){return this.throwIfDisposed(),Object(Ir.a)(this,e)};var Cr=n(211);Object(Nn.d)().prototype.prod=function(e,t){return this.throwIfDisposed(),Object(Cr.a)(this,e,t)};var Tr=n(274);Object(Nn.d)().prototype.reciprocal=function(){return this.throwIfDisposed(),Object(Tr.a)(this)};var Er=n(101);Object(Nn.d)().prototype.relu=function(){return this.throwIfDisposed(),Object(Er.a)(this)};var Ar=n(158);Object(Nn.d)().prototype.relu6=function(){return this.throwIfDisposed(),Object(Ar.a)(this)},Object(Nn.d)().prototype.reshapeAs=function(e){return this.throwIfDisposed(),Object(x.a)(this,e.shape)},Object(Nn.d)().prototype.reshape=function(e){return this.throwIfDisposed(),Object(x.a)(this,e)};var Rr=n(232);Object(Nn.d)().prototype.resizeBilinear=function(e,t,n){return this.throwIfDisposed(),Object(Rr.a)(this,e,t,n)};var Fr=n(230);Object(Nn.d)().prototype.resizeNearestNeighbor=function(e,t,n){return this.throwIfDisposed(),Object(Fr.a)(this,e,t,n)},Object(Nn.d)().prototype.reverse=function(e){return this.throwIfDisposed(),Object(Ft.a)(this,e)};var Dr=n(160);Object(Nn.d)().prototype.rfft=function(){return this.throwIfDisposed(),Object(Dr.a)(this)};var _r=n(213);Object(Nn.d)().prototype.round=function(){return this.throwIfDisposed(),Object(_r.a)(this)},Object(Nn.d)().prototype.rsqrt=function(){return this.throwIfDisposed(),Object(Re.a)(this)};var Mr=n(215);Object(Nn.d)().prototype.selu=function(){return this.throwIfDisposed(),Object(Mr.a)(this)};var zr=n(216);Object(Nn.d)().prototype.separableConv2d=function(e,t,n,r,a,i){return this.throwIfDisposed(),Object(zr.a)(this,e,t,n,r,a,i)},Object(Nn.d)().prototype.sigmoid=function(){return this.throwIfDisposed(),Object(Qt.a)(this)};var Lr=n(276);Object(Nn.d)().prototype.sign=function(){return this.throwIfDisposed(),Object(Lr.a)(this)},Object(Nn.d)().prototype.sin=function(){return this.throwIfDisposed(),Object(fe.a)(this)},Object(Nn.d)().prototype.sinh=function(){return this.throwIfDisposed(),Object(he.a)(this)},Object(Nn.d)().prototype.slice=function(e,t){return this.throwIfDisposed(),Object(lt.a)(this,e,t)};var Pr=n(277);Object(Nn.d)().prototype.softmax=function(e){return this.throwIfDisposed(),Object(Pr.a)(this,e)};var Br=n(205);Object(Nn.d)().prototype.softplus=function(){return this.throwIfDisposed(),Object(Br.a)(this)},Object(Nn.d)().prototype.spaceToBatchND=function(e,t){return this.throwIfDisposed(),Object(H.a)(this,e,t)},Object(Nn.d)().prototype.split=function(e,t){return this.throwIfDisposed(),Object(te.a)(this,e,t)},Object(Nn.d)().prototype.sqrt=function(){return this.throwIfDisposed(),Object(b.a)(this)},Object(Nn.d)().prototype.square=function(){return this.throwIfDisposed(),Object(m.a)(this)};var Wr=n(161);Object(Nn.d)().prototype.squaredDifference=function(e){return this.throwIfDisposed(),Object(Wr.a)(this,e)};var Ur=n(123);Object(Nn.d)().prototype.squeeze=function(e){return this.throwIfDisposed(),Object(Ur.a)(this,e)},Object(Nn.d)().prototype.stack=function(e,t){this.throwIfDisposed();var n=e instanceof Nn.a?[this,e]:[this].concat(Object(Vn.a)(e));return Object(hn.a)(n,t)},Object(Nn.d)().prototype.step=function(e){return this.throwIfDisposed(),Object(l.a)(this,e)};var Vr=n(278);Object(Nn.d)().prototype.stridedSlice=function(e,t,n,r,a,i,o,s){return this.throwIfDisposed(),Object(Vr.a)(this,e,t,n,r,a,i,o,s)},Object(Nn.d)().prototype.sub=function(e){return this.throwIfDisposed(),Object(v.a)(this,e)},Object(Nn.d)().prototype.sum=function(e,t){return this.throwIfDisposed(),Object(k.a)(this,e,t)};var Hr=n(279);Object(Nn.d)().prototype.tan=function(){return this.throwIfDisposed(),Object(Hr.a)(this)};var Gr=n(179);Object(Nn.d)().prototype.tanh=function(){return 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t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,{scale:2,mode:"fanIn",distribution:"normal",seed:null==e?null:e.seed})}return Object($r.a)(n,[{key:"getClassName",value:function(){return Di.className}}]),n}(Di);zi.className="HeNormal",i.Se.registerClass(zi);var Li=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,{scale:2,mode:"fanIn",distribution:"uniform",seed:null==e?null:e.seed})}return Object($r.a)(n,[{key:"getClassName",value:function(){return Di.className}}]),n}(Di);Li.className="HeUniform",i.Se.registerClass(Li);var Pi=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,{scale:1,mode:"fanIn",distribution:"normal",seed:null==e?null:e.seed})}return Object($r.a)(n,[{key:"getClassName",value:function(){return Di.className}}]),n}(Di);Pi.className="LeCunNormal",i.Se.registerClass(Pi);var Bi=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,{scale:1,mode:"fanIn",distribution:"uniform",seed:null==e?null:e.seed})}return Object($r.a)(n,[{key:"getClassName",value:function(){return Di.className}}]),n}(Di);Bi.className="LeCunNormal",i.Se.registerClass(Bi);var Wi=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),(r=t.call(this)).DEFAULT_GAIN=1,r.gain=null==e.gain?r.DEFAULT_GAIN:e.gain,r.seed=e.seed,null!=r.seed)throw new la("Random seed is not implemented for Orthogonal Initializer yet.");return r}return Object($r.a)(n,[{key:"apply",value:function(e,t){var n=this;return Object(i.pf)((function(){if(e.length<2)throw new la("Shape must be at least 2D.");e[0]*e[1]>2e3&&console.warn("Orthogonal initializer is being called on a matrix with more "+"than 2000 (".concat(e[0]*e[1],") elements: ")+"Slowness may result.");var t=bi(e[0]>e[1]?[e[1],e[0]]:e,0,1,"float32"),r=i.ke.gramSchmidt(t);return e[0]>e[1]&&(r=Object(i.sf)(r)),Object(i.ye)(n.gain,r)}))}},{key:"getConfig",value:function(){return{gain:this.gain,seed:this.seed}}}]),n}(Ni);Wi.className="Orthogonal",i.Se.registerClass(Wi);var Ui={constant:"Constant",glorotNormal:"GlorotNormal",glorotUniform:"GlorotUniform",heNormal:"HeNormal",heUniform:"HeUniform",identity:"Identity",leCunNormal:"LeCunNormal",leCunUniform:"LeCunUniform",ones:"Ones",orthogonal:"Orthogonal",randomNormal:"RandomNormal",randomUniform:"RandomUniform",truncatedNormal:"TruncatedNormal",varianceScaling:"VarianceScaling",zeros:"Zeros"};function Vi(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{};return ka(e,i.Se.SerializationMap.getMap().classNameMap,t,"initializer")}function Hi(e){return Oa(e)}function Gi(e){if("string"===typeof e){var t=e in Ui?Ui[e]:e;if("GlorotNormal"===t)return new Mi;if("GlorotUniform"===t)return new _i;if("HeNormal"===t)return new zi;if("HeUniform"===t)return new Li;if("LeCunNormal"===t)return new Pi;if("LeCunUniform"===t)return new Bi;var n={};return n.className=t,n.config={},Vi(n)}return e instanceof Ni?e:Vi(e)}var qi=0;function Ki(){return qi++}var Xi={};function Yi(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"";return e in Xi||(Xi[e]=0),Xi[e]+=1,e+Xi[e].toString()}function $i(e){return Array.isArray(e)&&Array.isArray(e[0])}function Qi(e){return 0===e.length?[]:Array.isArray(e[0])?e:[e]}function Zi(e){var t;if(Array.isArray(e)){if(1!==e.length)throw new ua("Expected Tensor length to be 1; got ".concat(e.length));t=e[0]}else t=e;return t}function Ji(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(1===e.length)return(e=e)[0];throw new ua("Expected exactly 1 Shape; got ".concat(e.length))}return e}function eo(e){var t,n=0,r=Object(ea.a)(e);try{for(r.s();!(t=r.n()).done;){var a=t.value;0===a.shape.length?n+=1:n+=a.shape.reduce((function(e,t){return e*t}))}}catch(i){r.e(i)}finally{r.f()}return n}var to="Variable",no=function(){function e(t){var n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"float32",r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:to,a=!(arguments.length>3&&void 0!==arguments[3])||arguments[3],o=arguments.length>4&&void 0!==arguments[4]?arguments[4]:null;Object(Yr.a)(this,e),this.dtype=null==n?"float32":n,this.shape=t.shape,this.id=Ki(),r=null==r?to:r,this.originalName=Za(r),this.name=Ja(this.originalName),this.trainable_=a,this.constraint=o,this.val=i.xf(t,this.trainable_,this.name,this.dtype)}return Object($r.a)(e,[{key:"read",value:function(){return this.assertNotDisposed(),this.val}},{key:"write",value:function(e){return this.assertNotDisposed(),function(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}(this.val,e),this.val.id!==e.id&&(this.val.assign(e),null!=this.constraint&&this.val.assign(this.constraint.apply(this.val))),this}},{key:"dispose",value:function(){this.assertNotDisposed(),this.val.dispose()}},{key:"assertNotDisposed",value:function(){if(this.val.isDisposed)throw new Error("LayersVariable ".concat(this.name," is already disposed."))}},{key:"trainable",get:function(){return this.trainable_},set:function(e){this.trainable_=e,this.val.trainable=e}}]),e}();function ro(e){return e.map((function(e){return e.read()}))}function ao(e){e.forEach((function(e){e[0].write(e[1])}))}var io=function e(t){Object(Yr.a)(this,e),this.dtype=t.dtype,this.shape=t.shape,null!=t.shape?this.ndim=t.shape.length:this.ndim=t.ndim,this.maxNDim=t.maxNDim,this.minNDim=t.minNDim,this.axes=t.axes||{}},oo=function e(t,n,r,a,i,o,s){Object(Yr.a)(this,e),this.dtype=t,this.shape=n,this.sourceLayer=r,this.inputs=a,this.callArgs=i,this.outputTensorIndex=s,this.id=Ki(),null!=o&&(this.originalName=Za(o),this.name=Ja(this.originalName)),this.rank=n.length},so=0,co=function(){function e(t,n){Object(Yr.a)(this,e),this.callArgs=n,this.id=so++,this.outboundLayer=t.outboundLayer,this.inboundLayers=t.inboundLayers,this.nodeIndices=t.nodeIndices,this.tensorIndices=t.tensorIndices,this.inputTensors=t.inputTensors,this.outputTensors=t.outputTensors,this.inputMasks=t.inputMasks,this.outputMasks=t.outputMasks,this.inputShapes=t.inputShapes,this.outputShapes=t.outputShapes;var r,a=Object(ea.a)(t.inboundLayers);try{for(a.s();!(r=a.n()).done;){var i=r.value;null!=i&&i.outboundNodes.push(this)}}catch(o){a.e(o)}finally{a.f()}t.outboundLayer.inboundNodes.push(this)}return Object($r.a)(e,[{key:"getConfig",value:function(){var e,t=[],n=Object(ea.a)(this.inboundLayers);try{for(n.s();!(e=n.n()).done;){var r=e.value;null!=r?t.push(r.name):t.push(null)}}catch(a){n.e(a)}finally{n.f()}return{outboundLayer:this.outboundLayer?this.outboundLayer.name:null,inboundLayers:t,nodeIndices:this.nodeIndices,tensorIndices:this.tensorIndices}}}]),e}(),uo=0,lo=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(){var e,r=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{};Object(Yr.a)(this,n),(e=t.call(this))._callHook=null,e._addedWeightNames=[],e._stateful=!1,e.id=uo++,e.activityRegularizer=null,e.inputSpec=null,e.supportsMasking=!1,e._trainableWeights=[],e._nonTrainableWeights=[],e._losses=[],e._updates=[],e._built=!1,e.inboundNodes=[],e.outboundNodes=[];var a=r.name;if(!a){var i=e.getClassName();a=va(i)+"_"+Yi(i)}if(e.name=a,e.trainable_=null==r.trainable||r.trainable,null!=r.inputShape||null!=r.batchInputShape){var o;if(null!=r.batchInputShape)o=r.batchInputShape;else if(null!=r.inputShape){var s=null;null!=r.batchSize&&(s=r.batchSize),o=[s].concat(r.inputShape)}e.batchInputShape=o;var c=r.dtype;null==c&&(c=r.inputDType),null==c&&(c="float32"),e.dtype=c}return null!=r.weights?e.initialWeights=r.weights:e.initialWeights=null,e._refCount=null,e.fastWeightInitDuringBuild=!1,e}return Object($r.a)(n,[{key:"getNodeAtIndex",value:function(e,t){if(0===this.inboundNodes.length)throw new ca("The layer has never been called "+"and thus has no defined ".concat(t,"."));if(this.inboundNodes.length<=e)throw new ua("Asked to get ".concat(t," at node ").concat(e,", ")+"but the layer has only ".concat(this.inboundNodes.length," inbound nodes."));return this.inboundNodes[e]}},{key:"getInputAt",value:function(e){return ba(this.getNodeAtIndex(e,"input").inputTensors)}},{key:"getOutputAt",value:function(e){return ba(this.getNodeAtIndex(e,"output").outputTensors)}},{key:"input",get:function(){if(this.inboundNodes.length>1)throw new sa("Layer ".concat(this.name)+' has multiple inbound nodes, hence the notion of "layer input" is ill-defined. Use `getInputAt(nodeIndex)` instead.');if(0===this.inboundNodes.length)throw new sa("Layer ".concat(this.name)+" is not connected, no input to return.");return ba(this.getNodeAtIndex(0,"input").inputTensors)}},{key:"output",get:function(){if(0===this.inboundNodes.length)throw new sa("Layer ".concat(this.name)+" has no inbound nodes.");if(this.inboundNodes.length>1)throw new sa("Layer ".concat(this.name)+' has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use `getOutputAt(nodeIndex)` instead.');return ba(this.getNodeAtIndex(0,"output").outputTensors)}},{key:"losses",get:function(){return this._losses}},{key:"calculateLosses",value:function(){return this.losses.map((function(e){return e()}))}},{key:"updates",get:function(){return this._updates}},{key:"built",get:function(){return this._built},set:function(e){this._built=e}},{key:"trainable",get:function(){return this.trainable_},set:function(e){this._trainableWeights.forEach((function(t){return t.trainable=e})),this.trainable_=e}},{key:"trainableWeights",get:function(){return this.trainable_?this._trainableWeights.filter((function(e){return e.trainable})):[]},set:function(e){this._trainableWeights=e}},{key:"nonTrainableWeights",get:function(){return this.trainable?this._trainableWeights.filter((function(e){return!e.trainable})).concat(this._nonTrainableWeights):this._trainableWeights.concat(this._nonTrainableWeights)},set:function(e){this._nonTrainableWeights=e}},{key:"weights",get:function(){return this.trainableWeights.concat(this.nonTrainableWeights)}},{key:"stateful",get:function(){return this._stateful}},{key:"resetStates",value:function(){if(!this.stateful)throw new Error("Cannot call the resetStates() method of a non-stateful Layer object.")}},{key:"assertInputCompatibility",value:function(e){if(e=ma(e),null!=this.inputSpec&&0!==this.inputSpec.length){var t=ma(this.inputSpec);if(e.length!==t.length)throw new ua("Layer ".concat(this.name," expects ").concat(t.length," inputs, ")+"but it received ".concat(e.length," input tensors. ")+"Input received: ".concat(e));for(var n=0;n<e.length;n++){var r=e[n],a=t[n];if(null!=a){var i=r.rank;if(null!=a.ndim&&i!==a.ndim)throw new ua("Input ".concat(n," is incompatible with layer ").concat(this.name,": ")+"expected ndim=".concat(a.ndim,", found ndim=").concat(i));if(null!=a.maxNDim&&i>a.maxNDim)throw new ua("Input ".concat(n," is incompatible with layer ").concat(this.name)+": expected max_ndim=".concat(a.maxNDim,", found ndim=").concat(i));if(null!=a.minNDim&&i<a.minNDim)throw new ua("Input ".concat(n," is incompatible with layer ").concat(this.name)+": expected min_ndim=".concat(a.minNDim,", found ndim=").concat(i,"."));if(null!=a.dtype&&r.dtype!==a.dtype)throw new ua("Input ".concat(n," is incompatible with layer ").concat(this.name," ")+": expected dtype=".concat(a.dtype,", found dtype=").concat(r.dtype,"."));if(a.axes){var o=r.shape;for(var s in a.axes){var c=Number(s),u=a.axes[s],l=c>=0?o[c]:o[o.length+c];if(null!=u&&-1===[u,null].indexOf(l))throw new ua("Input ".concat(n," is incompatible with layer ")+"".concat(this.name,": expected axis ").concat(c," of input shape to ")+"have value ".concat(u," but got shape ").concat(o,"."))}}if(null!=a.shape)for(var d=0;d<a.shape.length;++d){var f=a.shape[d],p=r.shape[d];if(null!=f&&null!=p&&f!==p)throw new ua("Input ".concat(n," is incompatible with layer ")+"".concat(this.name,": expected shape=").concat(a.shape,", ")+"found shape=".concat(r.shape,"."))}}}}}},{key:"call",value:function(e,t){return e}},{key:"invokeCallHook",value:function(e,t){null!=this._callHook&&this._callHook(e,t)}},{key:"setCallHook",value:function(e){this._callHook=e}},{key:"clearCallHook",value:function(){this._callHook=null}},{key:"apply",value:function(e,t){var n=this;t=t||{},this.assertNotDisposed();var r,a=ma(e),i=!0,o=Object(ea.a)(a);try{for(o.s();!(r=o.n()).done;){if(!(r.value instanceof oo)){i=!1;break}}}catch(l){o.e(l)}finally{o.f()}var s,c=!0,u=Object(ea.a)(a);try{for(u.s();!(s=u.n()).done;){if(s.value instanceof oo){c=!1;break}}}catch(l){u.e(l)}finally{u.f()}if(i===c)throw new ua("Arguments to apply() must be all SymbolicTensors or all Tensors");return Qa(this.name,(function(){if(!n.built){n.assertInputCompatibility(e);var r,i=[],o=Object(ea.a)(ma(e));try{for(o.s();!(r=o.n()).done;){var s=r.value;i.push(s.shape)}}catch(l){o.e(l)}finally{o.f()}n.build(ba(i)),n.built=!0,n.initialWeights&&n.setWeights(n.initialWeights),null===n._refCount&&c&&(n._refCount=1)}if(n.assertInputCompatibility(e),c){var u,d=n.call(e,t),f=ma(d),p=[],h=Object(ea.a)(f);try{for(h.s();!(u=h.n()).done;){var b=u.value;-1!==a.indexOf(b)&&(b=b.clone()),p.push(b)}}catch(l){h.e(l)}finally{h.f()}if(d=ba(p),null!=n.activityRegularizer)throw new la("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return d}var m,v=function(e){e=ma(e);var t,n=[],r=Object(ea.a)(e);try{for(r.s();!(t=r.n()).done;){var a=t.value;n.push(a.shape)}}catch(l){r.e(l)}finally{r.f()}return ba(n)}(e),g=n.computeOutputShape(v),y="float32";if(n.warnOnIncompatibleInputShape(Array.isArray(e)?v[0]:v),m=null!=g&&g.length>0&&Array.isArray(g[0])?g.map((function(r,a){return new oo(y,r,n,ma(e),t,n.name,a)})):new oo(y,g,n,ma(e),t,n.name),n.addInboundNode(e,m,null,null,v,g,t),n._refCount++,null!=n.activityRegularizer)throw new la("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return m}))}},{key:"warnOnIncompatibleInputShape",value:function(e){if(null!=this.batchInputShape)if(e.length!==this.batchInputShape.length)console.warn("The rank of the input tensor provided (shape: "+"".concat(JSON.stringify(e),") does not match that of the ")+"batchInputShape (".concat(JSON.stringify(this.batchInputShape),") ")+"of the layer ".concat(this.name));else{var t=!1;this.batchInputShape.forEach((function(n,r){null!=n&&null!=e[r]&&e[r]!==n&&(t=!0)})),t&&console.warn("The shape of the input tensor "+"(".concat(JSON.stringify(e),") does not ")+"match the expectation of layer ".concat(this.name,": ")+"".concat(JSON.stringify(this.batchInputShape)))}}},{key:"outputShape",get:function(){if(null==this.inboundNodes||0===this.inboundNodes.length)throw new sa("The layer ".concat(this.name," has never been called and thus has no ")+"defined output shape.");var e,t=[],n=Object(ea.a)(this.inboundNodes);try{for(n.s();!(e=n.n()).done;){var r=e.value,a=JSON.stringify(r.outputShapes);-1===t.indexOf(a)&&t.push(a)}}catch(o){n.e(o)}finally{n.f()}if(1===t.length){var i=this.inboundNodes[0].outputShapes;return Array.isArray(i)&&Array.isArray(i[0])&&1===i.length?i[0]:i}throw new sa("The layer ".concat(this.name," has multiple inbound nodes with different ")+'output shapes. Hence the notion of "output shape" is ill-defined for the layer.')}},{key:"countParams",value:function(){if(!this.built)throw new ca("You tried to call countParams() on ".concat(this.name,", ")+"but the layer is not built yet. Build it first by calling build(batchInputShape).");return eo(this.weights)}},{key:"build",value:function(e){this.built=!0}},{key:"getWeights",value:function(){var e=arguments.length>0&&void 0!==arguments[0]&&arguments[0];return ro(e?this.trainableWeights:this.weights)}},{key:"setWeights",value:function(e){var t=this;Object(i.pf)((function(){var n=t.weights;if(n.length!==e.length)throw new ua('You called setWeights(weights) on layer "'.concat(t.name,'" ')+"with a weight list of length ".concat(e.length,", ")+"but the layer was expecting ".concat(n.length," weights. 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t=[],n=null!=e&&e.trainableOnly,r=n?this.trainableWeights:this.weights,a=this.getWeights(n),i=0;i<r.length;++i)n&&!r[i].trainable||t.push({name:r[i].originalName,tensor:a[i]});return t}},{key:"stopTraining",get:function(){return this.stopTraining_},set:function(e){this.stopTraining_=e}},{key:"optimizer",get:function(){return this.optimizer_},set:function(e){this.optimizer_!==e&&(this.optimizer_=e,this.isOptimizerOwned=!1)}},{key:"dispose",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"dispose",this).call(this);if(0===e.refCountAfterDispose&&null!=this.optimizer&&this.isOptimizerOwned){var t=i.ve().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-i.ve().numTensors}return e}},{key:"getLossIdentifiers",value:function(){var e;if("string"===typeof this.loss)e=va(this.loss);else if(Array.isArray(this.loss)){var t,n=Object(ea.a)(this.loss);try{for(n.s();!(t=n.n()).done;){if("string"!==typeof t.value)throw new Error("Serialization of non-string loss is not 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")+"Input ".concat(v," (0-based) originates ")+"from layer type ".concat(g.getClassName(),"."));r.inputNames.push(g.name),r.feedInputShapes.push(g.batchInputShape),r.feedInputNames.push(g.name)}var y,O=Object(ea.a)(r.outputLayers);try{for(O.s();!(y=O.n()).done;){var x=y.value;r.outputNames.push(x.name)}}catch(ke){O.e(ke)}finally{O.f()}r.internalInputShapes=r.inputs.map((function(e){return e.shape})),r.internalOutputShapes=r.outputs.map((function(e){return e.shape}));var k,w={},j={},S={},N={},I={},C=[],T=function e(t,a,i,o,s,c){null!=o&&null!=s&&null!=c||(o=t.sourceLayer,s=t.nodeIndex,c=t.tensorIndex);var u=o.inboundNodes[s];if(-1!==i.indexOf(u))throw new ca("The tensor ".concat(t.name,' at layer "').concat(o.name,'" ')+"is part of a cycle.");if(-1===a.indexOf(u)){r.containerNodes.add(n.nodeKey(o,s)),o.id in I||(I[o.id]=Object.keys(I).length),-1===i.indexOf(u)&&i.push(u);for(var l=u.inboundLayers.length,d=0;d<l;d++){e(u.inputTensors[d],a,i,u.inboundLayers[d],u.nodeIndices[d],u.tensorIndices[d])}for(a.push(u);i.indexOf(u)>=0;)i.splice(i.indexOf(u),1);C.push(u)}},E=[],A=[],R=Object(ea.a)(r.outputs);try{for(R.s();!(k=R.n()).done;){T(k.value,E,A)}}catch(ke){R.e(ke)}finally{R.f()}var F,D=C.slice().reverse(),_=Object(ea.a)(D);try{for(_.s();!(F=_.n()).done;){var M=F.value;j[M.id]=M,M.id in w||(w[M.id]=0);var z=w[M.id],L=null==S[M.outboundLayer.id]?0:S[M.outboundLayer.id];z=Math.max(z,L),S[M.outboundLayer.id]=z,N[M.outboundLayer.id]=M.outboundLayer,w[M.id]=z;for(var P=0;P<M.inboundLayers.length;P++){var B=M.inboundLayers[P],W=M.nodeIndices[P],U=B.inboundNodes[W],V=null==w[U.id]?0:w[U.id];w[U.id]=Math.max(z+1,V),j[U.id]=U}}}catch(ke){_.e(ke)}finally{_.f()}var H={};for(var G in w){var q=w[G];q in H||(H[q]=[]),H[q].push(j[G])}var K={};for(var X in S){var Y=S[X];Y in K||(K[Y]=[]),K[Y].push(N[X])}var $=Object.keys(K).map((function(e){return parseInt(e,10)})).sort(wa);r.layers=[];var Q,Z=Object(ea.a)($);try{for(Z.s();!(Q=Z.n()).done;){var J=K[Q.value];J.sort((function(e,t){var n=I[e.id],r=I[t.id];return n<r?-1:n>r?1:0}));var ee,te=Object(ea.a)(J);try{for(te.s();!(ee=te.n()).done;){var ne=ee.value;ne instanceof n&&r.internalContainerRefs.push(ne),r.layers.push(ne)}}catch(ke){te.e(ke)}finally{te.f()}}}catch(ke){Z.e(ke)}finally{Z.f()}r.layersByDepth=K,$=Object.keys(H).map((function(e){return parseInt(e,10)})).sort(wa);var re,ae=r.inputs.slice(),ie=[],oe=Object(ea.a)($);try{for(oe.s();!(re=oe.n()).done;){var se,ce=re.value,ue=Object(ea.a)(H[ce]);try{for(ue.s();!(se=ue.n()).done;){var le=se.value,de=le.outboundLayer;if(null!=de){var fe,pe=Object(ea.a)(le.inputTensors);try{for(pe.s();!(fe=pe.n()).done;){var he=fe.value;if(-1===ae.indexOf(he))throw new ca("Graph disconnected: cannot obtain value for tensor ".concat(he)+' at layer "'.concat(de.name,'". ')+"The following previous layers were accessed without "+"issue: ".concat(ie))}}catch(ke){pe.e(ke)}finally{pe.f()}var be,me=Object(ea.a)(le.outputTensors);try{for(me.s();!(be=me.n()).done;){var ve=be.value;ae.push(ve)}}catch(ke){me.e(ke)}finally{me.f()}ie.push(de.name)}}}catch(ke){ue.e(ke)}finally{ue.f()}}}catch(ke){oe.e(ke)}finally{oe.f()}r.nodesByDepth=H;var ge,ye=r.layers.map((function(e){return e.name})),Oe=Object(ea.a)(ye);try{var xe=function(){var e=ge.value,t=ye.filter((function(t){return t===e})).length;if(1!==t)throw new ca('The name "'.concat(e,'" is used ').concat(t," times ")+"in the model. All layer names should be unique. 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Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];var e,t=[],n=Object(ea.a)(this.layers);try{for(n.s();!(e=n.n()).done;){var r=e.value;t=t.concat(r.trainableWeights)}}catch(a){n.e(a)}finally{n.f()}return t}},{key:"nonTrainableWeights",get:function(){var e,t=[],n=Object(ea.a)(this.layers);try{for(n.s();!(e=n.n()).done;){var r=e.value;t.push.apply(t,Object(Vn.a)(r.nonTrainableWeights))}}catch(c){n.e(c)}finally{n.f()}if(!this.trainable){var a,i=[],o=Object(ea.a)(this.layers);try{for(o.s();!(a=o.n()).done;){var s=a.value;i.push.apply(i,Object(Vn.a)(s.trainableWeights))}}catch(c){o.e(c)}finally{o.f()}return i.concat(t)}return t}},{key:"weights",get:function(){return this.trainableWeights.concat(this.nonTrainableWeights)}},{key:"loadWeights",value:function(e){var t,n=!(arguments.length>1&&void 0!==arguments[1])||arguments[1],r={},a=0,i=Object(ea.a)(this.layers);try{for(i.s();!(t=i.n()).done;){var o,s=t.value,c=Object(ea.a)(s.weights);try{for(c.s();!(o=c.n()).done;){var u=o.value;if(null!=r[u.originalName])throw new ua("Duplicate weight name: ".concat(u.originalName));r[u.originalName]=u,a++}}catch(v){c.e(v)}finally{c.f()}}}catch(v){i.e(v)}finally{i.f()}var l=[];for(var d in e){var f=d;if(null==r[d]){var p=d.split("/"),h=p.slice(0,-2).concat([p[p.length-1]]);f=h.join("/")}if(null!=r[f])l.push([r[f],e[d]]);else if(n)throw new ua("Provided weight data has no target variable: ".concat(d));delete r[f]}if(n){var b=[];for(var m in r)b.push(m);if(b.length>0)throw new ua("".concat(b.length," of ").concat(a," weights are not set: ")+"".concat(b))}ao(l)}},{key:"updatedConfig",value:function(){var e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion="tfjs-layers ".concat(ps),t.backend="TensorFlow.js",t}},{key:"toJSON",value:function(e){var t=!(arguments.length>1&&void 0!==arguments[1])||arguments[1],n=fs(this.updatedConfig());return t?JSON.stringify(n):n}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){e=ma(e);for(var r=new hs,a=0;a<n.inputs.length;++a)r.add(n.inputs[a],e[a]);return vs(n.outputs,r,t)}))}},{key:"computeMask",value:function(e,t){var n=this;return Object(i.pf)((function(){var r;return e=ma(e),r=null==t?fa(null,e.length):ma(t),n.runInternalGraph(e,r)[1]}))}},{key:"computeOutputShape",value:function(e){var t=Qi(e);if(t.length!==this.inputLayers.length)throw new ua("Invalid inputShape argument ".concat(e,": ")+"model has ".concat(this.inputLayers.length," tensor inputs."));for(var n={},r=0;r<t.length;r++){var a=this.inputLayers[r],i=t[r];n[a.name+"_0_0"]=i}var o=Object.keys(this.nodesByDepth).map((function(e){return parseInt(e,10)})).sort(wa);if(o.length>1){var s,c=Object(ea.a)(o);try{for(c.s();!(s=c.n()).done;){var u,l=s.value,d=this.nodesByDepth[l],f=Object(ea.a)(d);try{for(f.s();!(u=f.n()).done;){var p=u.value,h=p.outboundLayer;if(-1===this.inputLayers.map((function(e){return e.id})).indexOf(h.id)){for(var b=[],m=0;m<p.inboundLayers.length;m++){var v=p.inboundLayers[m],g=p.nodeIndices[m],y=p.tensorIndices[m],O=n["".concat(v.name,"_").concat(g,"_").concat(y)];b.push(O)}for(var x=Qi(h.computeOutputShape(ba(b))),k=h.inboundNodes.indexOf(p),w=0;w<x.length;w++){n["".concat(h.name,"_").concat(k,"_").concat(w)]=x[w]}}}}catch(F){f.e(F)}finally{f.f()}}}catch(F){c.e(F)}finally{c.f()}}for(var j=[],S=[],N=0;N<this.outputLayers.length;N++){var I=this.outputLayers[N],C=this.outputLayersNodeIndices[N],T=this.outputLayersTensorIndices[N],E="".concat(I.name,"_").concat(C,"_").concat(T);S.push(E)}for(var A=0;A<S.length;A++){var R=S[A];pa(R in n),j.push(n[R])}return ba(j)}},{key:"runInternalGraph",value:function(e,t){null==t&&(t=fa(null,e.length));for(var n={},r=0;r<this.inputs.length;++r){var a=this.inputs[r],i=e[r],s=t[r];n[a.id]=[i,s]}var c,u=Object.keys(this.nodesByDepth).map((function(e){return parseInt(e,10)})).sort(wa),l=Object(ea.a)(u);try{for(l.s();!(c=l.n()).done;){var d,f=c.value,p=this.nodesByDepth[f],h=Object(ea.a)(p);try{for(h.s();!(d=h.n()).done;){var b,m=d.value,v=m.outboundLayer,g=m.inputTensors,y=m.outputTensors,O=new Array,x=Object(ea.a)(g);try{for(x.s();!(b=x.n()).done;){var k=b.value;k.id in n&&O.push(n[k.id])}}catch(H){x.e(H)}finally{x.f()}if(O.length===g.length){var w={},j=void 0,S=void 0,N=void 0,I=void 0;if(null!=m.callArgs&&(w=m.callArgs),1===O.length){var C=Object(o.a)(O[0],2),T=C[0],E=C[1];null==w.mask&&(w.mask=E),N=ma(v.call(T,w)),I=ma(v.computeMask(T,E)),j=[T],S=[E]}else j=O.map((function(e){return e[0]})),S=O.map((function(e){return e[1]})),null==w.mask&&(w.mask=S),N=ma(v.call(j,w)),I=ma(v.computeMask(j,S));if(v.activityRegularizer)throw new la("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(var A=0;A<y.length;++A){var R=y[A],F=N[A],D=I[A];n[R.id]=[F,D]}}}}catch(H){h.e(H)}finally{h.f()}}}catch(H){l.e(H)}finally{l.f()}var _,M=[],z=[],L=[],P=Object(ea.a)(this.outputs);try{for(P.s();!(_=P.n()).done;){var B=_.value;pa(B.id in n,"Could not compute output ".concat(B.name," : ").concat(B.id));var W=Object(o.a)(n[B.id],2),U=W[0],V=W[1];L.push(U.shape),M.push(U),z.push(V)}}catch(H){P.e(H)}finally{P.f()}return[M,z,L]}},{key:"buildNodeConversionMap",value:function(e){var t,r,a={},i=Object(ea.a)(this.layers);try{for(i.s();!(r=i.n()).done;){var o=r.value;t=o instanceof n?1:0;for(var s=0;s<o.inboundNodes.length;s++){var c=n.nodeKey(o,s);this.containerNodes.has(c)&&(a[c]=t,t+=1)}}}catch(u){i.e(u)}finally{i.f()}return a}},{key:"getLayer",value:function(e,t){if(null!=t){if(this.layers.length<=t)throw new ua("Was asked to retrieve layer at index ".concat(t,", but model only ")+"has ".concat(this.layers.length," layer(s)."));return this.layers[t]}if(null==e)throw new ua("Provide either a layer name or layer index");var n,r=Object(ea.a)(this.layers);try{for(r.s();!(n=r.n()).done;){var a=n.value;if(a.name===e)return a}}catch(i){r.e(i)}finally{r.f()}throw new ua("No such layer: ".concat(e))}},{key:"calculateLosses",value:function(){var e=this;return Object(i.pf)((function(){var t,r=[],a=Object(ea.a)(e.layers);try{for(a.s();!(t=a.n()).done;)for(var i=t.value,o=0;o<i.inboundNodes.length;++o){var s=n.nodeKey(i,o);e.containerNodes.has(s)&&r.push.apply(r,Object(Vn.a)(i.calculateLosses()))}}catch(c){a.e(c)}finally{a.f()}return r}))}},{key:"getConfig",value:function(){var e,t={name:this.name},r=this.buildNodeConversionMap(this.layers),a=[],i=Object(ea.a)(this.layers);try{for(i.s();!(e=i.n()).done;){for(var o=e.value,s=o.getClassName(),c=o.getConfig(),u=[],l=0;l<o.inboundNodes.length;l++){var d=o.inboundNodes[l],f=n.nodeKey(o,l),p={};if(this.containerNodes.has(f)){if(d.callArgs)try{JSON.stringify(d.callArgs),p=d.callArgs}catch(_){console.warn("Layer ".concat(o.name," was passed ")+"non-serializable keyword arguments: "+"".concat(d.callArgs,". They will not be included ")+"in the serialized model (and thus will be missing at deserialization time)."),p={}}if(d.inboundLayers.length>0){for(var h=[],b=0;b<d.inboundLayers.length;b++){var m=d.inboundLayers[b],v=d.nodeIndices[b],g=d.tensorIndices[b],y=r[n.nodeKey(m,v)];null==y&&(y=0),h.push([m.name,y,g,p])}u.push(h)}}}var O={};O.name=o.name,O.className=s,O.config=c,O.inboundNodes=u,a.push(O)}}catch(_){i.e(_)}finally{i.f()}t.layers=a;for(var x=[],k=0;k<this.inputLayers.length;k++){var w=this.inputLayers[k],j=this.inputLayersNodeIndices[k],S=n.nodeKey(w,j);if(this.containerNodes.has(S)){var N=r[S];null!==N&&void 0!==N||(N=0);var I=this.inputLayersTensorIndices[k];x.push([w.name,N,I])}}t.inputLayers=x;for(var C=[],T=0;T<this.outputLayers.length;T++){var E=this.outputLayers[T],A=this.outputLayersNodeIndices[T],R=n.nodeKey(E,A);if(this.containerNodes.has(R)){var F=r[R];null!==F&&void 0!==F||(F=0);var D=this.outputLayersTensorIndices[T];C.push([E.name,F,D])}}return t.outputLayers=C,t}},{key:"stateful",get:function(){if(this._stateful)throw new ua("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");var e,t=Object(ea.a)(this.layers);try{for(t.s();!(e=t.n()).done;){if(e.value.stateful)return!0}}catch(n){t.e(n)}finally{t.f()}return!1}},{key:"resetStates",value:function(){var e=this;Object(i.pf)((function(){e.layers.forEach((function(e){e.stateful&&e.resetStates()}))}))}}],[{key:"fromConfig",value:function(e,t){var n=arguments.length>3&&void 0!==arguments[3]&&arguments[3],r={},a={};function i(e,t){e.name in a?a[e.name].push(t):a[e.name]=[t]}function o(e,t){var n,a,o=[],s=Object(ea.a)(t);try{for(s.s();!(a=s.n()).done;){var c=a.value,u=c[0],l=c[1],d=c[2];if(n=null==c[3]?{}:c[3],!(u in r))return void i(e,t);var f=r[u];if(f.inboundNodes.length<=l)return void i(e,t);var p=f.inboundNodes[l];o.push(p.outputTensors[d])}}catch(h){s.e(h)}finally{s.f()}o.length>0&&e.apply(ba(o),n)}function s(e){var a=e.name,o=Ao(e,null!=t.customObjects?t.customObjects:{});o.setFastWeightInitDuringBuild(n),r[a]=o,e.inboundNodes.forEach((function(e){if(!(e instanceof Array))throw new ua("Corrupted configuration, expected array for nodeData: ".concat(e));i(o,e)}))}var c,u=t.name,l=t.layers,d=Object(ea.a)(l);try{for(d.s();!(c=d.n()).done;){var f=c.value;s(f)}}catch(W){d.e(W)}finally{d.f()}for(;!Sa(a);){var p,h=Object(ea.a)(l);try{for(h.s();!(p=h.n()).done;){var b=p.value,m=r[b.name];if(m.name in a){var v=a[m.name];delete a[m.name];var g,y=Object(ea.a)(v);try{for(y.s();!(g=y.n()).done;){var O=g.value;o(m,O)}}catch(W){y.e(W)}finally{y.f()}}}}catch(W){h.e(W)}finally{h.f()}}var x,k=[],w=[],j=t.inputLayers,S=Object(ea.a)(j);try{for(S.s();!(x=S.n()).done;){var N=x.value,I=N[0],C=N[1],T=N[2];pa(I in r);var E=r[I],A=E.inboundNodes[C].outputTensors;k.push(A[T])}}catch(W){S.e(W)}finally{S.f()}var R,F=t.outputLayers,D=Object(ea.a)(F);try{for(D.s();!(R=D.n()).done;){var _=R.value,M=_[0],z=_[1],L=_[2];pa(M in r);var P=r[M],B=P.inboundNodes[z].outputTensors;w.push(B[L])}}catch(W){D.e(W)}finally{D.f()}return new e({inputs:k,outputs:w,name:u})}}]),n}(lo));Zs.className="Model",i.Se.registerClass(Zs);var Js=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(){return Object(Yr.a)(this,n),t.apply(this,arguments)}return n}(Zs);Js.className="Functional",i.Se.registerClass(Js);var ec=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),e=e||{},(r=t.call(this,{inputs:[],outputs:[]})).trainable=!0,r.built=!1,r.name=null!=e.name?e.name:Yi("sequential_"),null!=e.layers){var a,i=Object(ea.a)(e.layers);try{for(i.s();!(a=i.n()).done;){var o=a.value;r.add(o)}}catch(s){i.e(s)}finally{i.f()}}return r}return Object($r.a)(n,[{key:"checkShape",value:function(e){if(e.inboundNodes[0].outputTensors[0].shape.some((function(e){return e<0})))throw new ua("Negative dimension size caused by adding layer "+"".concat(e.name," with input shape [")+"".concat(e.inboundNodes[0].inputTensors[0].shape,"]"))}},{key:"add",value:function(e){var t,r=e instanceof n||e instanceof Zs;if(r){if(1!==(t=e).outputs.length)throw new ua("All layers in a Sequential model should have a single output tensor. 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For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[e.inboundNodes[0].outputTensors[0]],this.inputs=fo(this.outputs[0])}this.inboundNodes=[],new co({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:fa(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map((function(e){return e.shape})),outputShapes:this.outputs[0].shape})}else{var i=e.apply(this.outputs[0]);if(Array.isArray(i))throw new TypeError("All layers in a Sequential model should have a single output tensor. 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Received: ".concat(JSON.stringify(e)," including a")+" non-integer number ".concat(a))}return e;var i}function Dc(e,t,n,r){var a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:1;if(null==e)return e;var i,o=t+(t-1)*(a-1);return i="same"===n?e:e-o+1,Math.floor((i+r-1)/r)}function _c(e,t,n,r){if(null==e)return null;if("valid"===r)e=e*t+ai([n-t,0]);else{if("same"!==r)throw new ua("Unsupport padding mode: ".concat(r,"."));e*=t}return e}function Mc(e,t){return Object(i.pf)((function(){return Ka(t),"channelsFirst"===t?i.sf(e,[0,2,3,1]):e}))}function zc(e,t){return Object(i.pf)((function(){return Ka(t),"channelsFirst"===t?i.sf(e,[0,2,3,4,1]):e}))}function Lc(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:1,a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:"valid",o=arguments.length>5?arguments[5]:void 0,s=arguments.length>6&&void 0!==arguments[6]?arguments[6]:1;return Object(i.pf)((function(){if(null==o&&(o="channelsLast"),Ka(o),3!==e.shape.length)throw new ua("The input of a conv1dWithBias operation should be 3, but is "+"".concat(e.shape.length," instead."));if(3!==t.shape.length)throw new ua("The kernel for a conv1dWithBias operation should be 3, but is "+"".concat(t.shape.length," instead"));if(null!=n&&1!==n.shape.length)throw new ua("The bias for a conv1dWithBias operation should be 1, but is "+"".concat(t.shape.length," instead"));if("channelsFirst"===o&&(e=i.sf(e,[0,2,1])),"causal"===a)throw new la("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");var c=i.Id(e,t,r,"same"===a?"same":"valid","NWC",s);return null!=n&&(c=Oi(c,n)),c}))}function Pc(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:[1,1],a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:"valid",o=arguments.length>5?arguments[5]:void 0,s=arguments.length>6?arguments[6]:void 0,c=arguments.length>7&&void 0!==arguments[7]?arguments[7]:null;return Object(i.pf)((function(){if(null==o&&(o="channelsLast"),Ka(o),3!==e.rank&&4!==e.rank)throw new ua("conv2dWithBiasActivation expects input to be of rank 3 or 4, "+"but received ".concat(e.rank,"."));if(3!==t.rank&&4!==t.rank)throw new ua("conv2dWithBiasActivation expects kernel to be of rank 3 or 4, "+"but received ".concat(e.rank,"."));var u=Mc(e,o);if("causal"===a)throw new la("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return u=i.be.conv2d({x:u,filter:t,strides:r,pad:"same"===a?"same":"valid",dilations:s,dataFormat:"NHWC",bias:n,activation:c}),"channelsFirst"===o&&(u=i.sf(u,[0,3,1,2])),u}))}function Bc(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:[1,1,1],a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:"valid",o=arguments.length>5?arguments[5]:void 0,s=arguments.length>6?arguments[6]:void 0;return Object(i.pf)((function(){if(null==o&&(o="channelsLast"),Ka(o),4!==e.rank&&5!==e.rank)throw new ua("conv3dWithBias expects input to be of rank 4 or 5, but received "+"".concat(e.rank,"."));if(4!==t.rank&&5!==t.rank)throw new ua("conv3dWithBias expects kernel to be of rank 4 or 5, but received "+"".concat(e.rank,"."));var c=zc(e,o);if("causal"===a)throw new la("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return c=i.Ld(c,t,r,"same"===a?"same":"valid","NDHWC",s),null!=n&&(c=Oi(c,n)),"channelsFirst"===o&&(c=i.sf(c,[0,4,1,2,3])),c}))}var Wc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e,r){var a;if(Object(Yr.a)(this,n),(a=t.call(this,r)).bias=null,a.DEFAULT_KERNEL_INITIALIZER="glorotNormal",a.DEFAULT_BIAS_INITIALIZER="zeros",n.verifyArgs(r),a.rank=e,Ca(a.rank,"rank"),1!==a.rank&&2!==a.rank&&3!==a.rank)throw new la("Convolution layer for rank other than 1, 2, or 3 (".concat(a.rank,") is ")+"not implemented yet.");if(a.kernelSize=Fc(r.kernelSize,e,"kernelSize"),a.strides=Fc(null==r.strides?1:r.strides,e,"strides"),a.padding=null==r.padding?"valid":r.padding,Xa(a.padding),a.dataFormat=null==r.dataFormat?"channelsLast":r.dataFormat,Ka(a.dataFormat),a.activation=gc(r.activation),a.useBias=null==r.useBias||r.useBias,a.biasInitializer=Gi(r.biasInitializer||a.DEFAULT_BIAS_INITIALIZER),a.biasConstraint=Ba(r.biasConstraint),a.biasRegularizer=Sc(r.biasRegularizer),a.activityRegularizer=Sc(r.activityRegularizer),a.dilationRate=Fc(null==r.dilationRate?1:r.dilationRate,e,"dilationRate"),1===a.rank&&Array.isArray(a.dilationRate)&&1!==a.dilationRate.length)throw new ua("dilationRate must be a number or an array of a single number for 1D convolution, but received "+"".concat(JSON.stringify(a.dilationRate)));if(2===a.rank){if("number"===typeof a.dilationRate)a.dilationRate=[a.dilationRate,a.dilationRate];else if(2!==a.dilationRate.length)throw new ua("dilationRate must be a number or array of two numbers for 2D "+"convolution, but received ".concat(JSON.stringify(a.dilationRate)))}else if(3===a.rank)if("number"===typeof a.dilationRate)a.dilationRate=[a.dilationRate,a.dilationRate,a.dilationRate];else if(3!==a.dilationRate.length)throw new ua("dilationRate must be a number or array of three numbers for 3D "+"convolution, but received ".concat(JSON.stringify(a.dilationRate)));return a}return Object($r.a)(n,[{key:"getConfig",value:function(){var e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:mc(this.activation),useBias:this.useBias,biasInitializer:Hi(this.biasInitializer),biasRegularizer:wc(this.biasRegularizer),activityRegularizer:wc(this.activityRegularizer),biasConstraint:La(this.biasConstraint)},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}],[{key:"verifyArgs",value:function(e){if(pa("kernelSize"in e,"required key 'kernelSize' not in config"),"number"!==typeof e.kernelSize&&!Ia(e.kernelSize,"number",1,3))throw new ua("BaseConv expects config.kernelSize to be number or number[] with "+"length 1, 2, or 3, but received ".concat(JSON.stringify(e.kernelSize),"."))}}]),n}(lo),Uc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e,r){var a;return Object(Yr.a)(this,n),(a=t.call(this,e,r)).kernel=null,n.verifyArgs(r),a.filters=r.filters,Ca(a.filters,"filters"),a.kernelInitializer=Gi(r.kernelInitializer||a.DEFAULT_KERNEL_INITIALIZER),a.kernelConstraint=Ba(r.kernelConstraint),a.kernelRegularizer=Sc(r.kernelRegularizer),a}return Object($r.a)(n,[{key:"build",value:function(e){e=Ji(e);var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new ua("The channel dimension of the input should be defined. "+"Found ".concat(e[t]));var n=e[t],r=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",r,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:Object(Rc.a)({},t,n)}],this.built=!0}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var t;e=Zi(e);var r=null==n.bias?null:n.bias.read(),a=Ea(n.activation.getClassName());if(null!=a&&2===n.rank)t=Pc(e,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate,a);else{if(1===n.rank)t=Lc(e,n.kernel.read(),r,n.strides[0],n.padding,n.dataFormat,n.dilationRate[0]);else if(2===n.rank)t=Pc(e,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate);else{if(3!==n.rank)throw new la("convolutions greater than 3D are not implemented yet.");t=Bc(e,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate)}null!=n.activation&&(t=n.activation.apply(t))}return t}))}},{key:"computeOutputShape",value:function(e){e=Ji(e);for(var t=[],n="channelsLast"===this.dataFormat?e.slice(1,e.length-1):e.slice(2),r=0;r<n.length;++r){var a=Dc(n[r],this.kernelSize[r],this.padding,this.strides[r],"number"===typeof this.dilationRate?this.dilationRate:this.dilationRate[r]);t.push(a)}var i=[e[0]];return"channelsLast"===this.dataFormat?(i=i.concat(t)).push(this.filters):(i.push(this.filters),i=i.concat(t)),i}},{key:"getConfig",value:function(){var e={filters:this.filters,kernelInitializer:Hi(this.kernelInitializer),kernelRegularizer:wc(this.kernelRegularizer),kernelConstraint:La(this.kernelConstraint)},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}],[{key:"verifyArgs",value:function(e){if(!("filters"in e)||"number"!==typeof e.filters||e.filters<1)throw new ua("Convolution layer expected config.filters to be a 'number' > 0 "+"but got ".concat(JSON.stringify(e.filters)))}}]),n}(Wc),Vc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),r=t.call(this,2,e),n.verifyArgs(e),r}return Object($r.a)(n,[{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return delete e.rank,e}}],[{key:"verifyArgs",value:function(e){if("number"!==typeof e.kernelSize&&!Ia(e.kernelSize,"number",1,2))throw new ua("Conv2D expects config.kernelSize to be number or number[] with "+"length 1 or 2, but received ".concat(JSON.stringify(e.kernelSize),"."))}}]),n}(Uc);Vc.className="Conv2D",i.Se.registerClass(Vc);var Hc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),r=t.call(this,3,e),n.verifyArgs(e),r}return Object($r.a)(n,[{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return delete e.rank,e}}],[{key:"verifyArgs",value:function(e){if("number"!==typeof e.kernelSize&&(!Array.isArray(e.kernelSize)||1!==e.kernelSize.length&&3!==e.kernelSize.length))throw new ua("Conv3D expects config.kernelSize to be number or"+" [number, number, number], but received ".concat(JSON.stringify(e.kernelSize),"."))}}]),n}(Uc);Hc.className="Conv3D",i.Se.registerClass(Hc);var Gc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),(r=t.call(this,e)).inputSpec=[new io({ndim:4})],"same"!==r.padding&&"valid"!==r.padding)throw new ua("Conv2DTranspose currently supports only padding modes 'same' "+"and 'valid', but received padding mode ".concat(r.padding));return r}return Object($r.a)(n,[{key:"build",value:function(e){if(4!==(e=Ji(e)).length)throw new ua("Input should have rank 4; Received input shape: "+JSON.stringify(e));var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new ua("The channel dimension of the inputs should be defined. Found `None`.");var n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new io({ndim:4,axes:Object(Rc.a)({},t,n)})],this.built=!0}},{key:"call",value:function(e,t){var n=this;return i.pf((function(){var t=Zi(e);if(4!==t.shape.length)throw new ua("Conv2DTranspose.call() expects input tensor to be rank-4, but "+"received a tensor of rank-".concat(t.shape.length));var r,a,o=t.shape,s=o[0];"channelsFirst"===n.dataFormat?(r=2,a=3):(r=1,a=2);var c=o[r],u=o[a],l=n.kernelSize[0],d=n.kernelSize[1],f=n.strides[0],p=n.strides[1],h=[s,_c(c,f,l,n.padding),_c(u,p,d,n.padding),n.filters];"channelsLast"!==n.dataFormat&&(t=i.sf(t,[0,2,3,1]));var b=i.Kd(t,n.kernel.read(),h,n.strides,n.padding);return"channelsLast"!==n.dataFormat&&(b=i.sf(b,[0,3,1,2])),null!=n.bias&&(b=Oi(b,n.bias.read(),n.dataFormat)),null!=n.activation&&(b=n.activation.apply(b)),b}))}},{key:"computeOutputShape",value:function(e){var t,n,r,a=(e=Ji(e)).slice();"channelsFirst"===this.dataFormat?(t=1,n=2,r=3):(t=3,n=1,r=2);var i=this.kernelSize[0],o=this.kernelSize[1],s=this.strides[0],c=this.strides[1];return a[t]=this.filters,a[n]=_c(a[n],s,i,this.padding),a[r]=_c(a[r],c,o,this.padding),a}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return delete e.dilationRate,e}}]),n}(Vc);Gc.className="Conv2DTranspose",i.Se.registerClass(Gc);var qc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),(r=t.call(this,e)).inputSpec=[new io({ndim:5})],"same"!==r.padding&&"valid"!==r.padding)throw new ua("Conv3DTranspose currently supports only padding modes 'same' "+"and 'valid', but received padding mode ".concat(r.padding));return r}return Object($r.a)(n,[{key:"build",value:function(e){if(5!==(e=Ji(e)).length)throw new ua("Input should have rank 5; Received input shape: "+JSON.stringify(e));var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new ua("The channel dimension of the inputs should be defined. Found `None`.");var n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new io({ndim:5,axes:Object(Rc.a)({},t,n)})],this.built=!0}},{key:"call",value:function(e,t){var n=this;return i.pf((function(){var t=Zi(e);if(5!==t.shape.length)throw new ua("Conv3DTranspose.call() expects input tensor to be rank-4, but "+"received a tensor of rank-".concat(t.shape.length));var r,a,o,s=t.shape,c=s[0];"channelsFirst"===n.dataFormat?(o=2,r=3,a=4):(o=1,r=2,a=3);var u=s[o],l=s[r],d=s[a],f=n.kernelSize[0],p=n.kernelSize[1],h=n.kernelSize[2],b=n.strides[0],m=n.strides[1],v=n.strides[2],g=[c,_c(u,b,f,n.padding),_c(l,m,p,n.padding),_c(d,v,h,n.padding),n.filters];"channelsLast"!==n.dataFormat&&(t=i.sf(t,[0,2,3,4,1]));var y=i.Md(t,n.kernel.read(),g,n.strides,n.padding);return"channelsLast"!==n.dataFormat&&(y=i.sf(y,[0,4,1,2,3])),null!==n.bias&&(y=Oi(y,n.bias.read(),n.dataFormat)),null!==n.activation&&(y=n.activation.apply(y)),y}))}},{key:"computeOutputShape",value:function(e){var t,n,r,a,i=(e=Ji(e)).slice();"channelsFirst"===this.dataFormat?(t=1,n=2,r=3,a=4):(t=4,n=1,r=2,a=3);var o=this.kernelSize[0],s=this.kernelSize[1],c=this.kernelSize[2],u=this.strides[0],l=this.strides[1],d=this.strides[2];return i[t]=this.filters,i[n]=_c(i[n],u,o,this.padding),i[r]=_c(i[r],l,s,this.padding),i[a]=_c(i[a],d,c,this.padding),i}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return delete e.dilationRate,e}}]),n}(Hc);qc.className="Conv3DTranspose",i.Se.registerClass(qc);var Kc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e,r){var a;if(Object(Yr.a)(this,n),(a=t.call(this,e,r)).DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",a.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",a.depthwiseKernel=null,a.pointwiseKernel=null,null==r.filters)throw new ua("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(null!=r.kernelInitializer||null!=r.kernelRegularizer||null!=r.kernelConstraint)throw new ua("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(null!=r.padding&&"same"!==r.padding&&"valid"!==r.padding)throw new ua("SeparableConv".concat(a.rank,"D supports only padding modes: ")+"'same' and 'valid', but received ".concat(JSON.stringify(r.padding)));return a.depthMultiplier=null==r.depthMultiplier?1:r.depthMultiplier,a.depthwiseInitializer=Gi(r.depthwiseInitializer||a.DEFAULT_DEPTHWISE_INITIALIZER),a.depthwiseRegularizer=Sc(r.depthwiseRegularizer),a.depthwiseConstraint=Ba(r.depthwiseConstraint),a.pointwiseInitializer=Gi(r.depthwiseInitializer||a.DEFAULT_POINTWISE_INITIALIZER),a.pointwiseRegularizer=Sc(r.pointwiseRegularizer),a.pointwiseConstraint=Ba(r.pointwiseConstraint),a}return Object($r.a)(n,[{key:"build",value:function(e){if((e=Ji(e)).length<this.rank+2)throw new ua("Inputs to SeparableConv".concat(this.rank,"D should have rank ")+"".concat(this.rank+2,", but received input shape: ")+"".concat(JSON.stringify(e)));var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t]||e[t]<0)throw new ua("The channel dimension of the inputs should be defined, "+"but found ".concat(JSON.stringify(e[t])));for(var n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[],i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);var o=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,o,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,o,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,o,this.biasConstraint):this.bias=null,this.inputSpec=[new io({ndim:this.rank+2,axes:Object(Rc.a)({},t,n)})],this.built=!0}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var t;if(e=Zi(e),1===n.rank)throw new la("1D separable convolution is not implemented yet.");return 2===n.rank&&("channelsFirst"===n.dataFormat&&(e=i.sf(e,[0,2,3,1])),t=i.Re(e,n.depthwiseKernel.read(),n.pointwiseKernel.read(),n.strides,n.padding,n.dilationRate,"NHWC")),n.useBias&&(t=Oi(t,n.bias.read(),n.dataFormat)),null!=n.activation&&(t=n.activation.apply(t)),"channelsFirst"===n.dataFormat&&(t=i.sf(t,[0,3,1,2])),t}))}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Hi(this.depthwiseInitializer),e.pointwiseInitializer=Hi(this.pointwiseInitializer),e.depthwiseRegularizer=wc(this.depthwiseRegularizer),e.pointwiseRegularizer=wc(this.pointwiseRegularizer),e.depthwiseConstraint=La(this.depthwiseConstraint),e.pointwiseConstraint=La(this.pointwiseConstraint),e}}]),n}(Uc);Kc.className="SeparableConv";var Xc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,2,e)}return n}(Kc);Xc.className="SeparableConv2D",i.Se.registerClass(Xc);var Yc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),r=t.call(this,1,e),n.verifyArgs(e),r.inputSpec=[{ndim:3}],r}return Object($r.a)(n,[{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return delete e.rank,delete e.dataFormat,e}}],[{key:"verifyArgs",value:function(e){if("number"!==typeof e.kernelSize&&!Ia(e.kernelSize,"number",1,1))throw new ua("Conv1D expects config.kernelSize to be number or number[] with "+"length 1, but received ".concat(JSON.stringify(e.kernelSize),"."))}}]),n}(Uc);Yc.className="Conv1D",i.Se.registerClass(Yc);var $c=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),r=t.call(this,e),"number"===typeof e.cropping?r.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:"number"===typeof e.cropping[0]?r.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:r.cropping=e.cropping,r.dataFormat=void 0===e.dataFormat?"channelsLast":e.dataFormat,r.inputSpec=[{ndim:4}],r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){return"channelsFirst"===this.dataFormat?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){if(e=Zi(e),"channelsLast"===n.dataFormat){var t=di(e,n.cropping[0][0],e.shape[1]-n.cropping[0][0]-n.cropping[0][1],2);return di(t,n.cropping[1][0],e.shape[2]-n.cropping[1][1]-n.cropping[1][0],3)}var r=di(e,n.cropping[0][0],e.shape[2]-n.cropping[0][0]-n.cropping[0][1],3);return di(r,n.cropping[1][0],e.shape[3]-n.cropping[1][1]-n.cropping[1][0],4)}))}},{key:"getConfig",value:function(){var e={cropping:this.cropping,dataFormat:this.dataFormat},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);$c.className="Cropping2D",i.Se.registerClass($c);var Qc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r,a;return Object(Yr.a)(this,n),(r=t.call(this,e)).DEFAULT_SIZE=[2,2],r.inputSpec=[{ndim:4}],r.size=null==e.size?r.DEFAULT_SIZE:e.size,r.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,Ka(r.dataFormat),r.interpolation=null==e.interpolation?"nearest":e.interpolation,a=r.interpolation,Na(Ua,"InterpolationFormat",a),r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){if("channelsFirst"===this.dataFormat){var t=null==e[2]?null:this.size[0]*e[2],n=null==e[3]?null:this.size[1]*e[3];return[e[0],e[1],t,n]}var r=null==e[1]?null:this.size[0]*e[1],a=null==e[2]?null:this.size[1]*e[2];return[e[0],r,a,e[3]]}},{key:"call",value:function(e,t){var n=this;return i.pf((function(){var t=Zi(e),r=t.shape;if("channelsFirst"===n.dataFormat){t=i.sf(t,[0,2,3,1]);var a=n.size[0]*r[2],o=n.size[1]*r[3],s="nearest"===n.interpolation?i.fe.resizeNearestNeighbor(t,[a,o]):i.fe.resizeBilinear(t,[a,o]);return i.sf(s,[0,3,1,2])}var c=n.size[0]*r[1],u=n.size[1]*r[2];return"nearest"===n.interpolation?i.fe.resizeNearestNeighbor(t,[c,u]):i.fe.resizeBilinear(t,[c,u])}))}},{key:"getConfig",value:function(){var e={size:this.size,dataFormat:this.dataFormat},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);Qc.className="UpSampling2D",i.Se.registerClass(Qc);var Zc=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,2,e)).depthwiseKernel=null,r.depthMultiplier=null==e.depthMultiplier?1:e.depthMultiplier,r.depthwiseInitializer=Gi(e.depthwiseInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.depthwiseConstraint=Ba(e.depthwiseConstraint),r.depthwiseRegularizer=Sc(e.depthwiseRegularizer),r}return Object($r.a)(n,[{key:"build",value:function(e){if((e=Ji(e)).length<4)throw new ua("Inputs to DepthwiseConv2D should have rank 4. "+"Received input shape: ".concat(JSON.stringify(e),"."));var t="channelsFirst"===this.dataFormat?1:3;if(null==e[t]||e[t]<0)throw new ua("The channel dimension of the inputs to DepthwiseConv2D should "+"be defined, but is not (".concat(e[t],")."));var n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var t=function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:[1,1],r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:"valid",a=arguments.length>4?arguments[4]:void 0,o=arguments.length>5?arguments[5]:void 0;return Object(i.pf)((function(){null==a&&(a="channelsLast"),Ka(a);var s=Mc(e,a);if(4!==e.rank)throw new ua("Input for depthwiseConv2d is required to be 4-D, but is instead "+"".concat(e.rank,"-D"));if(4!==t.rank)throw new ua("depthwiseKernel is required to be 4-D, but is instead "+"".concat(t.rank,"-D"));return s=i.Nd(s,t,n,"same"===r?"same":"valid","NHWC",o),"channelsFirst"===a&&(s=i.sf(s,[0,3,1,2])),s}))}(e=Zi(e),n.depthwiseKernel.read(),n.strides,n.padding,n.dataFormat,null);return n.useBias&&(t=Oi(t,n.bias.read(),n.dataFormat)),null!=n.activation&&(t=n.activation.apply(t)),t}))}},{key:"computeOutputShape",value:function(e){e=Ji(e);var t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2],r="channelsFirst"===this.dataFormat?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Dc(t,this.kernelSize[0],this.padding,this.strides[0]),i=Dc(n,this.kernelSize[1],this.padding,this.strides[1]);return"channelsFirst"===this.dataFormat?[e[0],r,a,i]:[e[0],a,i,r]}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Hi(this.depthwiseInitializer),e.depthwiseRegularizer=wc(this.depthwiseRegularizer),e.depthwiseConstraint=La(this.depthwiseRegularizer),e}}]),n}(Wc);function Jc(e,t,n,r){if(Array.isArray(e)){if(null!=t||null!=n)throw new ua("When inputs is an array, neither initialState or constants should be provided");null!=r&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(e){return null==e||Array.isArray(e)?e:[e]}return{inputs:e,initialState:t=a(t),constants:n=a(n)}}function eu(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]&&arguments[3],a=arguments.length>4?arguments[4]:void 0,o=arguments.length>5?arguments[5]:void 0,s=arguments.length>6&&void 0!==arguments[6]&&arguments[6],c=arguments.length>7&&void 0!==arguments[7]&&arguments[7];return i.pf((function(){var u=t.shape.length;if(u<3)throw new ua("Input should be at least 3D, but is ".concat(u,"D."));var l=[1,0].concat(ii(2,u));if(t=i.sf(t,l),null!=o)throw new la("The rnn() functoin of the deeplearn.js backend does not support constants yet.");s&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),null!=a&&((a=i.Ad(i.Ad(a,"bool"),"float32")).rank===u-1&&(a=i.Xd(a,-1)),a=i.sf(a,l)),r&&(t=i.Oe(t,0),null!=a&&(a=i.Oe(a,0)));var d,f,p=[],h=n,b=t.shape[0],m=i.uf(t);null!=a&&(f=i.uf(a));for(var v,g=function(t){var n=m[t],r=i.pf((function(){return e(n,h)}));if(null==a)d=r[0],h=r[1];else{var o=i.pf((function(){var e=f[t],n=i.hf(i.Ee(e),e);return{output:i.nd(i.ye(r[0],e),i.ye(h[0],n)),newStates:h.map((function(t,a){return i.nd(i.ye(r[1][a],e),i.ye(t,n))}))}}));d=o.output,h=o.newStates}c&&p.push(d)},y=0;y<b;++y)g(y);if(c){v=i.gf(p,1)}return[d,v,h]}))}Zc.className="DepthwiseConv2D",i.Se.registerClass(Zc);var tu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r,a;if(Object(Yr.a)(this,n),r=t.call(this,e),null==e.cell)throw new ua("cell property is missing for the constructor of RNN.");if(null==(a=Array.isArray(e.cell)?new uu({cells:e.cell}):e.cell).stateSize)throw new ua("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");return r.cell=a,r.returnSequences=null!=e.returnSequences&&e.returnSequences,r.returnState=null!=e.returnState&&e.returnState,r.goBackwards=null!=e.goBackwards&&e.goBackwards,r._stateful=null!=e.stateful&&e.stateful,r.unroll=null!=e.unroll&&e.unroll,r.supportsMasking=!0,r.inputSpec=[new io({ndim:3})],r.stateSpec=null,r.states_=null,r.numConstants=null,r.keptStates=[],r}return Object($r.a)(n,[{key:"getStates",value:function(){return null==this.states_?ii(0,Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1).map((function(e){return null})):this.states_}},{key:"setStates",value:function(e){this.states_=e}},{key:"computeOutputShape",value:function(e){$i(e)&&(e=e[0]),e=e;var t=this.cell.stateSize;Array.isArray(t)||(t=[t]);var n,r=t[0];if(n=this.returnSequences?[e[0],e[1],r]:[e[0],r],this.returnState){var a,i=[],o=Object(ea.a)(t);try{for(o.s();!(a=o.n()).done;){var s=a.value;i.push([e[0],s])}}catch(c){o.e(c)}finally{o.f()}return[n].concat(i)}return n}},{key:"computeMask",value:function(e,t){var n=this;return i.pf((function(){Array.isArray(t)&&(t=t[0]);var e=n.returnSequences?t:null;if(n.returnState){var r=n.states.map((function(e){return null}));return[e].concat(r)}return e}))}},{key:"states",get:function(){if(null==this.states_){for(var e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[],n=0;n<e;++n)t.push(null);return t}return this.states_},set:function(e){this.states_=e}},{key:"build",value:function(e){if(null!=this.numConstants)throw new la("Constants support is not implemented in RNN yet.");$i(e)&&(e=e[0]),e=e;var t=this.stateful?e[0]:null,n=e.slice(2);this.inputSpec[0]=new io({shape:[t,null].concat(Object(Vn.a)(n))});var r,a=[e[0]].concat(e.slice(2));if(this.cell.build(a),r=Array.isArray(this.cell.stateSize)?this.cell.stateSize:[this.cell.stateSize],null!=this.stateSpec){if(!i.wf.arraysEqual(this.stateSpec.map((function(e){return e.shape[e.shape.length-1]})),r))throw new ua("An initialState was passed that is not compatible with "+"cell.stateSize. Received stateSpec=".concat(this.stateSpec,"; ")+"However cell.stateSize is ".concat(this.cell.stateSize))}else this.stateSpec=r.map((function(e){return new io({shape:[null,e]})}));this.stateful&&this.resetStates()}},{key:"resetStates",value:function(e){var t=this,n=arguments.length>1&&void 0!==arguments[1]&&arguments[1];Object(i.pf)((function(){if(!t.stateful)throw new sa("Cannot call resetStates() on an RNN Layer that is not stateful.");var r=t.inputSpec[0].shape[0];if(null==r)throw new ua("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(null==t.states_)Array.isArray(t.cell.stateSize)?t.states_=t.cell.stateSize.map((function(e){return i.Bf([r,e])})):t.states_=[i.Bf([r,t.cell.stateSize])];else if(null==e)i.Pd(t.states_),null!=t.keptStates&&(i.Pd(t.keptStates),t.keptStates=[]),Array.isArray(t.cell.stateSize)?t.states_=t.cell.stateSize.map((function(e){return i.Bf([r,e])})):t.states_[0]=i.Bf([r,t.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==t.states_.length)throw new ua("Layer ".concat(t.name," expects ").concat(t.states_.length," state(s), ")+"but it received ".concat(e.length," state value(s). Input ")+"received: ".concat(e));!0===n?t.keptStates.push(t.states_.slice()):i.Pd(t.states_);for(var a=0;a<t.states_.length;++a){var o=e[a],s=Array.isArray(t.cell.stateSize)?t.cell.stateSize[a]:t.cell.stateSize,c=[r,s];if(!i.wf.arraysEqual(o.shape,c))throw new ua("State ".concat(a," is incompatible with layer ").concat(t.name,": ")+"expected shape=".concat(c,", received shape=").concat(o.shape));t.states_[a]=o}}t.states_=t.states_.map((function(e){return i.he(e.clone())}))}))}},{key:"apply",value:function(e,t){var r=null==t?null:t.initialState,a=null==t?null:t.constants;null==t&&(t={});var i=Jc(e,r,a,this.numConstants);e=i.inputs,r=i.initialState,a=i.constants;var o=[],s=[];if(null!=r){t.initialState=r,o=o.concat(r),this.stateSpec=[];var c,u=Object(ea.a)(r);try{for(u.s();!(c=u.n()).done;){var l=c.value;this.stateSpec.push(new io({shape:l.shape}))}}catch(b){u.e(b)}finally{u.f()}s=s.concat(this.stateSpec)}if(null!=a&&(t.constants=a,o=o.concat(a),this.numConstants=a.length),o[0]instanceof oo){var d=[e].concat(o),f=this.inputSpec.concat(s),p=this.inputSpec;this.inputSpec=f;var h=Object(Eo.a)(Object(na.a)(n.prototype),"apply",this).call(this,d,t);return this.inputSpec=p,h}return Object(Eo.a)(Object(na.a)(n.prototype),"apply",this).call(this,e,t)}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var r=null==t?null:t.mask,a=null==t?null:t.training,i=null==t?null:t.initialState;e=Zi(e),null==i&&(i=n.stateful?n.states_:n.getInitialState(e));var o=Array.isArray(n.cell.stateSize)?n.cell.stateSize.length:1;if(i.length!==o)throw new ua("RNN Layer has ".concat(o," state(s) but was passed ")+"".concat(i.length," initial state(s)."));n.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");var s={training:a},c=eu((function(e,t){var r=n.cell.call([e].concat(t),s);return[r[0],r.slice(1)]}),e,i,n.goBackwards,r,null,n.unroll,n.returnSequences),u=c[0],l=c[1],d=c[2];n.stateful&&n.resetStates(d,a);var f=n.returnSequences?l:u;return n.returnState?[f].concat(d):f}))}},{key:"getInitialState",value:function(e){var t=this;return Object(i.pf)((function(){var n=i.Bf(e.shape);return n=si(n=i.if(n,[1,2])),Array.isArray(t.cell.stateSize)?t.cell.stateSize.map((function(e){return e>1?hi(n,[1,e]):n})):t.cell.stateSize>1?[hi(n,[1,t.cell.stateSize])]:[n]}))}},{key:"trainableWeights",get:function(){return this.trainable?this.cell.trainableWeights:[]}},{key:"nonTrainableWeights",get:function(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}},{key:"setFastWeightInitDuringBuild",value:function(e){Object(Eo.a)(Object(na.a)(n.prototype),"setFastWeightInitDuringBuild",this).call(this,e),null!=this.cell&&this.cell.setFastWeightInitDuringBuild(e)}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};null!=this.numConstants&&(t.numConstants=this.numConstants);var r=this.cell.getConfig();return this.getClassName()===n.className&&(t.cell={className:this.cell.getClassName(),config:r}),Object.assign({},r,e,t)}}],[{key:"fromConfig",value:function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{},r=t.cell,a=Ao(r,n);return new e(Object.assign(t,{cell:a}))}}]),n}(lo);tu.className="RNN",i.Se.registerClass(tu);var nu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(){return Object(Yr.a)(this,n),t.apply(this,arguments)}return n}(lo),ru=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).DEFAULT_ACTIVATION="tanh",r.DEFAULT_KERNEL_INITIALIZER="glorotNormal",r.DEFAULT_RECURRENT_INITIALIZER="orthogonal",r.DEFAULT_BIAS_INITIALIZER="zeros",r.units=e.units,Ca(r.units,"units"),r.activation=gc(null==e.activation?r.DEFAULT_ACTIVATION:e.activation),r.useBias=null==e.useBias||e.useBias,r.kernelInitializer=Gi(e.kernelInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.recurrentInitializer=Gi(e.recurrentInitializer||r.DEFAULT_RECURRENT_INITIALIZER),r.biasInitializer=Gi(e.biasInitializer||r.DEFAULT_BIAS_INITIALIZER),r.kernelRegularizer=Sc(e.kernelRegularizer),r.recurrentRegularizer=Sc(e.recurrentRegularizer),r.biasRegularizer=Sc(e.biasRegularizer),r.kernelConstraint=Ba(e.kernelConstraint),r.recurrentConstraint=Ba(e.recurrentConstraint),r.biasConstraint=Ba(e.biasConstraint),r.dropout=ri([1,ai([0,null==e.dropout?0:e.dropout])]),r.recurrentDropout=ri([1,ai([0,null==e.recurrentDropout?0:e.recurrentDropout])]),r.stateSize=r.units,r.dropoutMask=null,r.recurrentDropoutMask=null,r}return Object($r.a)(n,[{key:"build",value:function(e){e=Ji(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){if(2!==(e=e).length)throw new ua("SimpleRNNCell expects 2 input Tensors, got ".concat(e.length,"."));var r=e[1];e=e[0];var a,o=null!=t.training&&t.training;0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=lu({ones:function(){return i.Ee(e)},rate:n.dropout,training:o})),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=lu({ones:function(){return i.Ee(r)},rate:n.recurrentDropout,training:o}));var s=n.dropoutMask,c=n.recurrentDropoutMask;a=mi(null!=s?i.ye(e,s):e,n.kernel.read()),null!=n.bias&&(a=Oi(a,n.bias.read())),null!=c&&(r=i.ye(r,c));var u=i.nd(a,mi(r,n.recurrentKernel.read()));return null!=n.activation&&(u=n.activation.apply(u)),[u,u]}))}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t={units:this.units,activation:mc(this.activation),useBias:this.useBias,kernelInitializer:Hi(this.kernelInitializer),recurrentInitializer:Hi(this.recurrentInitializer),biasInitializer:Hi(this.biasInitializer),kernelRegularizer:wc(this.kernelRegularizer),recurrentRegularizer:wc(this.recurrentRegularizer),biasRegularizer:wc(this.biasRegularizer),activityRegularizer:wc(this.activityRegularizer),kernelConstraint:La(this.kernelConstraint),recurrentConstraint:La(this.recurrentConstraint),biasConstraint:La(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}}]),n}(nu);ru.className="SimpleRNNCell",i.Se.registerClass(ru);var au=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),e.cell=new ru(e),t.call(this,e)}return Object($r.a)(n,[{key:"call",value:function(e,t){var r=this;return Object(i.pf)((function(){null!=r.cell.dropoutMask&&(i.Pd(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(i.Pd(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null);var a=null==t?null:t.mask,o=null==t?null:t.training,s=null==t?null:t.initialState;return Object(Eo.a)(Object(na.a)(n.prototype),"call",r).call(r,e,{mask:a,training:o,initialState:s})}))}}],[{key:"fromConfig",value:function(e,t){return new e(t)}}]),n}(tu);au.className="SimpleRNN",i.Se.registerClass(au);var iu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),(r=t.call(this,e)).DEFAULT_ACTIVATION="tanh",r.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",r.DEFAULT_KERNEL_INITIALIZER="glorotNormal",r.DEFAULT_RECURRENT_INITIALIZER="orthogonal",r.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new ua("GRUCell does not support reset_after parameter set to true.");return r.units=e.units,Ca(r.units,"units"),r.activation=gc(void 0===e.activation?r.DEFAULT_ACTIVATION:e.activation),r.recurrentActivation=gc(void 0===e.recurrentActivation?r.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),r.useBias=null==e.useBias||e.useBias,r.kernelInitializer=Gi(e.kernelInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.recurrentInitializer=Gi(e.recurrentInitializer||r.DEFAULT_RECURRENT_INITIALIZER),r.biasInitializer=Gi(e.biasInitializer||r.DEFAULT_BIAS_INITIALIZER),r.kernelRegularizer=Sc(e.kernelRegularizer),r.recurrentRegularizer=Sc(e.recurrentRegularizer),r.biasRegularizer=Sc(e.biasRegularizer),r.kernelConstraint=Ba(e.kernelConstraint),r.recurrentConstraint=Ba(e.recurrentConstraint),r.biasConstraint=Ba(e.biasConstraint),r.dropout=ri([1,ai([0,null==e.dropout?0:e.dropout])]),r.recurrentDropout=ri([1,ai([0,null==e.recurrentDropout?0:e.recurrentDropout])]),r.implementation=e.implementation,r.stateSize=r.units,r.dropoutMask=null,r.recurrentDropoutMask=null,r}return Object($r.a)(n,[{key:"build",value:function(e){var t=(e=Ji(e))[e.length-1];this.kernel=this.addWeight("kernel",[t,3*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,3*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[3*this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){if(2!==(e=e).length)throw new ua("GRUCell expects 2 input Tensors (inputs, h, c), got "+"".concat(e.length,"."));var r=null!=t.training&&t.training,a=e[1];e=e[0],0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=lu({ones:function(){return i.Ee(e)},rate:n.dropout,training:r,count:3})),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=lu({ones:function(){return i.Ee(a)},rate:n.recurrentDropout,training:r,count:3}));var s,c,u,l=n.dropoutMask,d=n.recurrentDropoutMask;0<n.dropout&&n.dropout<1&&(e=i.ye(e,l[0]));var f=mi(e,n.kernel.read());n.useBias&&(f=Oi(f,n.bias.read())),0<n.recurrentDropout&&n.recurrentDropout<1&&(a=i.ye(a,d[0]));var p=n.recurrentKernel.read(),h=i.df(p,[2*n.units,n.units],p.rank-1),b=Object(o.a)(h,2),m=b[0],v=b[1],g=mi(a,m),y=i.df(f,3,f.rank-1),O=Object(o.a)(y,3),x=O[0],k=O[1],w=O[2],j=i.df(g,2,g.rank-1),S=Object(o.a)(j,2),N=S[0],I=S[1];s=n.recurrentActivation.apply(i.nd(x,N)),c=n.recurrentActivation.apply(i.nd(k,I));var C=mi(i.ye(c,a),v);u=n.activation.apply(i.nd(w,C));var T=i.nd(i.ye(s,a),i.ye(i.nd(1,i.ze(s)),u));return[T,T]}))}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t={units:this.units,activation:mc(this.activation),recurrentActivation:mc(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Hi(this.kernelInitializer),recurrentInitializer:Hi(this.recurrentInitializer),biasInitializer:Hi(this.biasInitializer),kernelRegularizer:wc(this.kernelRegularizer),recurrentRegularizer:wc(this.recurrentRegularizer),biasRegularizer:wc(this.biasRegularizer),activityRegularizer:wc(this.activityRegularizer),kernelConstraint:La(this.kernelConstraint),recurrentConstraint:La(this.recurrentConstraint),biasConstraint:La(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}}]),n}(nu);iu.className="GRUCell",i.Se.registerClass(iu);var ou=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),0===e.implementation&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new iu(e),t.call(this,e)}return Object($r.a)(n,[{key:"call",value:function(e,t){var r=this;return Object(i.pf)((function(){null!=r.cell.dropoutMask&&(i.Pd(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(i.Pd(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null);var a=null==t?null:t.mask,o=null==t?null:t.training,s=null==t?null:t.initialState;return Object(Eo.a)(Object(na.a)(n.prototype),"call",r).call(r,e,{mask:a,training:o,initialState:s})}))}}],[{key:"fromConfig",value:function(e,t){return 0===t.implmentation&&(t.implementation=1),new e(t)}}]),n}(tu);ou.className="GRU",i.Se.registerClass(ou);var su=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).DEFAULT_ACTIVATION="tanh",r.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",r.DEFAULT_KERNEL_INITIALIZER="glorotNormal",r.DEFAULT_RECURRENT_INITIALIZER="orthogonal",r.DEFAULT_BIAS_INITIALIZER="zeros",r.units=e.units,Ca(r.units,"units"),r.activation=gc(void 0===e.activation?r.DEFAULT_ACTIVATION:e.activation),r.recurrentActivation=gc(void 0===e.recurrentActivation?r.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),r.useBias=null==e.useBias||e.useBias,r.kernelInitializer=Gi(e.kernelInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.recurrentInitializer=Gi(e.recurrentInitializer||r.DEFAULT_RECURRENT_INITIALIZER),r.biasInitializer=Gi(e.biasInitializer||r.DEFAULT_BIAS_INITIALIZER),r.unitForgetBias=e.unitForgetBias,r.kernelRegularizer=Sc(e.kernelRegularizer),r.recurrentRegularizer=Sc(e.recurrentRegularizer),r.biasRegularizer=Sc(e.biasRegularizer),r.kernelConstraint=Ba(e.kernelConstraint),r.recurrentConstraint=Ba(e.recurrentConstraint),r.biasConstraint=Ba(e.biasConstraint),r.dropout=ri([1,ai([0,null==e.dropout?0:e.dropout])]),r.recurrentDropout=ri([1,ai([0,null==e.recurrentDropout?0:e.recurrentDropout])]),r.implementation=e.implementation,r.stateSize=[r.units,r.units],r.dropoutMask=null,r.recurrentDropoutMask=null,r}return Object($r.a)(n,[{key:"build",value:function(e){var t,n,r=(e=Ji(e))[e.length-1];if(this.kernel=this.addWeight("kernel",[r,4*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,4*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){if(this.unitForgetBias){var a=this.biasInitializer,i=this.units;n=new((t=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(){return Object(Yr.a)(this,n),t.apply(this,arguments)}return Object($r.a)(n,[{key:"apply",value:function(e,t){var n=a.apply([i]),r=(new Ci).apply([i]),o=a.apply([2*i]);return pi(pi(n,r),o)}}]),n}(Ni)).className="CustomInit",t)}else n=this.biasInitializer;this.bias=this.addWeight("bias",[4*this.units],null,n,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var r=null!=t.training&&t.training;if(3!==(e=e).length)throw new ua("LSTMCell expects 3 input Tensors (inputs, h, c), got "+"".concat(e.length,"."));var a=e[1],s=e[2];e=e[0],0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=lu({ones:function(){return i.Ee(e)},rate:n.dropout,training:r,count:4})),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=lu({ones:function(){return i.Ee(a)},rate:n.recurrentDropout,training:r,count:4}));var c,u,l,d,f=n.dropoutMask,p=n.recurrentDropoutMask;0<n.dropout&&n.dropout<1&&(e=i.ye(e,f[0]));var h=mi(e,n.kernel.read());0<n.recurrentDropout&&n.recurrentDropout<1&&(a=i.ye(a,p[0])),h=i.nd(h,mi(a,n.recurrentKernel.read())),n.useBias&&(h=Oi(h,n.bias.read()));var b=i.df(h,4,h.rank-1),m=Object(o.a)(b,4),v=m[0],g=m[1],y=m[2],O=m[3];c=n.recurrentActivation.apply(v),u=n.recurrentActivation.apply(g),l=i.nd(i.ye(u,s),i.ye(c,n.activation.apply(y))),d=n.recurrentActivation.apply(O);var x=i.ye(d,n.activation.apply(l));return[x,x,l]}))}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t={units:this.units,activation:mc(this.activation),recurrentActivation:mc(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Hi(this.kernelInitializer),recurrentInitializer:Hi(this.recurrentInitializer),biasInitializer:Hi(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:wc(this.kernelRegularizer),recurrentRegularizer:wc(this.recurrentRegularizer),biasRegularizer:wc(this.biasRegularizer),activityRegularizer:wc(this.activityRegularizer),kernelConstraint:La(this.kernelConstraint),recurrentConstraint:La(this.recurrentConstraint),biasConstraint:La(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}}]),n}(nu);su.className="LSTMCell",i.Se.registerClass(su);var cu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),0===e.implementation&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new su(e),t.call(this,e)}return Object($r.a)(n,[{key:"call",value:function(e,t){var r=this;return Object(i.pf)((function(){null!=r.cell.dropoutMask&&(i.Pd(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(i.Pd(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null);var a=null==t?null:t.mask,o=null==t?null:t.training,s=null==t?null:t.initialState;return Object(Eo.a)(Object(na.a)(n.prototype),"call",r).call(r,e,{mask:a,training:o,initialState:s})}))}}],[{key:"fromConfig",value:function(e,t){return 0===t.implmentation&&(t.implementation=1),new e(t)}}]),n}(tu);cu.className="LSTM",i.Se.registerClass(cu);var uu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).cells=e.cells,r}return Object($r.a)(n,[{key:"stateSize",get:function(){var e,t=[],n=Object(ea.a)(this.cells.slice().reverse());try{for(n.s();!(e=n.n()).done;){var r=e.value;Array.isArray(r.stateSize)?t.push.apply(t,Object(Vn.a)(r.stateSize)):t.push(r.stateSize)}}catch(a){n.e(a)}finally{n.f()}return t}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var r,a=(e=e).slice(1),i=[],o=Object(ea.a)(n.cells.slice().reverse());try{for(o.s();!(r=o.n()).done;){var s=r.value;Array.isArray(s.stateSize)?i.push(a.splice(0,s.stateSize.length)):i.push(a.splice(0,1))}}catch(m){o.e(m)}finally{o.f()}i.reverse();for(var c,u=[],l=0;l<n.cells.length;++l){var d=n.cells[l];a=i[l],c=0===l?[e[0]].concat(a):[c[0]].concat(a),c=d.call(c,t),u.push(c.slice(1))}a=[];var f,p=Object(ea.a)(u.slice().reverse());try{for(p.s();!(f=p.n()).done;){var h,b=f.value;(h=a).push.apply(h,Object(Vn.a)(b))}}catch(m){p.e(m)}finally{p.f()}return[c[0]].concat(a)}))}},{key:"build",value:function(e){var t;$i(e)&&(e=e[0]),e=e,this.cells.forEach((function(n,r){Qa("RNNCell_".concat(r),(function(){n.build(e),t=Array.isArray(n.stateSize)?n.stateSize[0]:n.stateSize,e=[e[0],t]}))})),this.built=!0}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t={cells:this.cells.map((function(e){return{className:e.getClassName(),config:e.getConfig()}}))};return Object.assign({},e,t)}},{key:"trainableWeights",get:function(){if(!this.trainable)return[];var e,t=[],n=Object(ea.a)(this.cells);try{for(n.s();!(e=n.n()).done;){var r=e.value;t.push.apply(t,Object(Vn.a)(r.trainableWeights))}}catch(a){n.e(a)}finally{n.f()}return t}},{key:"nonTrainableWeights",get:function(){var e,t=[],n=Object(ea.a)(this.cells);try{for(n.s();!(e=n.n()).done;){var r=e.value;t.push.apply(t,Object(Vn.a)(r.nonTrainableWeights))}}catch(c){n.e(c)}finally{n.f()}if(!this.trainable){var a,i=[],o=Object(ea.a)(this.cells);try{for(o.s();!(a=o.n()).done;){var s=a.value;i.push.apply(i,Object(Vn.a)(s.trainableWeights))}}catch(c){o.e(c)}finally{o.f()}return i.concat(t)}return t}},{key:"getWeights",value:function(){var e,t=[],n=Object(ea.a)(this.cells);try{for(n.s();!(e=n.n()).done;){var r=e.value;t.push.apply(t,Object(Vn.a)(r.weights))}}catch(a){n.e(a)}finally{n.f()}return ro(t)}},{key:"setWeights",value:function(e){var t,n=[],r=Object(ea.a)(this.cells);try{for(r.s();!(t=r.n()).done;)for(var a=t.value,i=a.weights.length,o=e.splice(i),s=0;s<a.weights.length;++s)n.push([a.weights[s],o[s]])}catch(c){r.e(c)}finally{r.f()}ao(n)}}],[{key:"fromConfig",value:function(e,t){var n,r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{},a=[],i=Object(ea.a)(t.cells);try{for(i.s();!(n=i.n()).done;){var o=n.value;a.push(Ao(o,r))}}catch(s){i.e(s)}finally{i.f()}return new e({cells:a})}}]),n}(nu);function lu(e){var t=e.ones,n=e.rate,r=e.training,a=void 0!==r&&r,o=e.count,s=void 0===o?1:o,c=function(){return ki(t(),n)},u=function(){return wi(c,t,a)};return!s||s<=1?i.he(u().clone()):Array(s).fill(void 0).map(u).map((function(e){return i.he(e.clone())}))}uu.className="StackedRNNCells",i.Se.registerClass(uu);var du=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(null!=e&&"function"===typeof Object.getOwnPropertySymbols){var a=0;for(r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]])}return n},fu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),e.unroll)throw new la("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new la("It is not possible at the moment to stack convolutional cells.");return(r=t.call(this,e)).inputSpec=[new io({ndim:5})],r}return Object($r.a)(n,[{key:"call",value:function(e,t){var r=this;return i.pf((function(){if(null!=r.cell.dropoutMask&&(i.Pd(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(i.Pd(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null),t&&t.constants)throw new ua("ConvRNN2D cell does not support constants");var a=null==t?null:t.mask,o=null==t?null:t.training,s=null==t?null:t.initialState;return Object(Eo.a)(Object(na.a)(n.prototype),"call",r).call(r,e,{mask:a,training:o,initialState:s})}))}},{key:"computeOutputShape",value:function(e){var t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0]].concat(Object(Vn.a)(t.slice(2)))),this.returnState&&(t=[t].concat(Object(Vn.a)(Array(2).fill([e[0]].concat(Object(Vn.a)(t.slice(-3))))))),t}},{key:"getInitialState",value:function(e){var t=this;return i.pf((function(){var n=t.cell.stateSize,r=e.shape,a=t.computeSingleOutputShape(r),o=[a[0]].concat(Object(Vn.a)(a.slice(2))),s=i.Bf(o);return Array.isArray(n)?Array(n.length).fill(s):[s]}))}},{key:"resetStates",value:function(e){var t=this,n=arguments.length>1&&void 0!==arguments[1]&&arguments[1];i.pf((function(){if(!t.stateful)throw new sa("Cannot call resetStates() on an RNN Layer that is not stateful.");var r=t.inputSpec[0].shape,a=t.computeSingleOutputShape(r),o=[a[0]].concat(Object(Vn.a)(a.slice(2)));if(null==r[0])throw new ua("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(null==t.getStates())Array.isArray(t.cell.stateSize)?t.states_=t.cell.stateSize.map((function(){return i.Bf(o)})):t.states_=[i.Bf(o)];else if(null==e)i.Pd(t.states_),null!=t.keptStates&&(i.Pd(t.keptStates),t.keptStates=[]),Array.isArray(t.cell.stateSize)?t.states_=t.cell.stateSize.map((function(){return i.Bf(o)})):t.states_[0]=i.Bf(o);else{if(Array.isArray(e)||(e=[e]),e.length!==t.states_.length)throw new ua("Layer ".concat(t.name," expects ").concat(t.states_.length," state(s), ")+"but it received ".concat(e.length," state value(s). Input ")+"received: ".concat(e));n?t.keptStates.push(t.states_.slice()):i.Pd(t.states_);for(var s=0;s<t.states_.length;++s){var c=e[s],u=o;if(!i.wf.arraysEqual(c.shape,u))throw new ua("State ".concat(s," is incompatible with layer ").concat(t.name,": ")+"expected shape=".concat(u,", received shape=").concat(c.shape));t.states_[s]=c}}t.states_=t.states_.map((function(e){return i.he(e.clone())}))}))}},{key:"computeSingleOutputShape",value:function(e){var t=this.cell,n=t.dataFormat,r=t.filters,a=t.kernelSize,i=t.padding,o=t.strides,s=t.dilationRate,c="channelsFirst"===n,u=e[c?3:2],l=e[c?4:3],d=Dc(u,a[0],i,o[0],s[0]),f=Dc(l,a[1],i,o[1],s[1]);return[].concat(Object(Vn.a)(e.slice(0,2)),Object(Vn.a)(c?[r,d,f]:[d,f,r]))}}]),n}(tu);fu.className="ConvRNN2D";var pu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;Object(Yr.a)(this,n);var a=e.filters,i=e.kernelSize,o=e.strides,s=e.padding,c=e.dataFormat,u=e.dilationRate;return(r=t.call(this,Object.assign({},e,{units:a}))).filters=a,Ca(r.filters,"filters"),r.kernelSize=Fc(i,2,"kernelSize"),r.kernelSize.forEach((function(e){return Ca(e,"kernelSize")})),r.strides=Fc(o||1,2,"strides"),r.strides.forEach((function(e){return Ca(e,"strides")})),r.padding=s||"valid",Xa(r.padding),r.dataFormat=c||"channelsLast",Ka(r.dataFormat),r.dilationRate=Fc(u||1,2,"dilationRate"),r.dilationRate.forEach((function(e){return Ca(e,"dilationRate")})),r}return Object($r.a)(n,[{key:"build",value:function(e){var t;e=Ji(e);var n="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[n])throw new ua("The channel dimension of the input should be defined. "+"Found ".concat(e[n]));var r=e[n],a=this.kernelSize.concat([r,4*this.filters]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);var o=this.kernelSize.concat([this.filters,4*this.filters]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",o,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){var s;if(this.unitForgetBias){var c=this.biasInitializer,u=this.filters;s=new((t=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(){return Object(Yr.a)(this,n),t.apply(this,arguments)}return Object($r.a)(n,[{key:"apply",value:function(e,t){return fi([c.apply([u]),i.De([u]),c.apply([2*u])])}}]),n}(Ni)).className="CustomInit",t)}else s=this.biasInitializer;this.bias=this.addWeight("bias",[4*this.filters],null,s,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}},{key:"call",value:function(e,t){var n=this;return i.pf((function(){if(3!==e.length)throw new ua("ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got "+"".concat(e.length,"."));var r=t.training||!1,a=e[0],s=e[1],c=e[2];0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=lu({ones:function(){return i.Ee(a)},rate:n.dropout,training:r,count:4}));var u=n.dropoutMask,l=function(e,t,n){return t&&t[n]?i.ye(t[n],e):e},d=l(a,u,0),f=l(a,u,1),p=l(a,u,2),h=l(a,u,3);0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=lu({ones:function(){return i.Ee(s)},rate:n.recurrentDropout,training:r,count:4}));var b=n.recurrentDropoutMask,m=l(s,b,0),v=l(s,b,1),g=l(s,b,2),y=l(s,b,3),O=i.df(n.kernel.read(),4,3),x=Object(o.a)(O,4),k=x[0],w=x[1],j=x[2],S=x[3],N=n.useBias?i.df(n.bias.read(),4):[null,null,null,null],I=Object(o.a)(N,4),C=I[0],T=I[1],E=I[2],A=I[3];d=n.inputConv(d,k,C,n.padding),f=n.inputConv(f,w,T,n.padding),p=n.inputConv(p,j,E,n.padding),h=n.inputConv(h,S,A,n.padding);var R=i.df(n.recurrentKernel.read(),4,3),F=Object(o.a)(R,4),D=F[0],_=F[1],M=F[2],z=F[3];m=n.recurrentConv(m,D),v=n.recurrentConv(v,_),g=n.recurrentConv(g,M),y=n.recurrentConv(y,z);var L=n.recurrentActivation.apply(i.nd(d,m)),P=n.recurrentActivation.apply(i.nd(f,v)),B=i.nd(i.ye(P,c),i.ye(L,n.activation.apply(i.nd(p,g)))),W=i.ye(n.recurrentActivation.apply(i.nd(h,y)),n.activation.apply(B));return[W,W,B]}))}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t=(e.units,du(e,["units"])),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},t,r)}},{key:"inputConv",value:function(e,t,n,r){var a=i.Jd(e,t,this.strides,r||"valid","channelsFirst"===this.dataFormat?"NCHW":"NHWC",this.dilationRate);return n?Oi(a,n,this.dataFormat):a}},{key:"recurrentConv",value:function(e,t){return i.Jd(e,t,1,"same","channelsFirst"===this.dataFormat?"NCHW":"NHWC")}}]),n}(su);pu.className="ConvLSTM2DCell",i.Se.registerClass(pu);var hu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){Object(Yr.a)(this,n);var r=new pu(e);return t.call(this,Object.assign({},e,{cell:r}))}return Object($r.a)(n,null,[{key:"fromConfig",value:function(e,t){return new e(t)}}]),n}(fu);hu.className="ConvLSTM2D",i.Se.registerClass(hu);var bu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).rate=Math.max(Math.min(e.rate,1),0),r.noiseShape=e.noiseShape,r.seed=e.seed,r.supportsMasking=!0,r}return Object($r.a)(n,[{key:"getNoiseShape",value:function(e){if(null==this.noiseShape)return this.noiseShape;for(var t=e.shape,n=[],r=0;r<this.noiseShape.length;++r)n.push(null==this.noiseShape[r]?t[r]:this.noiseShape[r]);return n}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t);var r=Zi(e);if(0<n.rate&&n.rate<1){var a=null!=t.training&&t.training,i=n.getNoiseShape(r);return wi((function(){return ki(r,n.rate,i,n.seed)}),(function(){return r}),a)}return e}))}},{key:"getConfig",value:function(){var e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}},{key:"dispose",value:function(){return Object(Eo.a)(Object(na.a)(n.prototype),"dispose",this).call(this)}}]),n}(lo);bu.className="Dropout",i.Se.registerClass(bu);var mu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).inputSpec=[{ndim:3}],r}return Object($r.a)(n,[{key:"getNoiseShape",value:function(e){var t=e.shape;return[t[0],1,t[2]]}}]),n}(bu);mu.className="SpatialDropout1D",i.Se.registerClass(mu);var vu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),(r=t.call(this,e)).activation=null,r.useBias=!0,r.kernel=null,r.bias=null,r.DEFAULT_KERNEL_INITIALIZER="glorotNormal",r.DEFAULT_BIAS_INITIALIZER="zeros",null==e.batchInputShape&&null==e.inputShape&&null!=e.inputDim){var a=null;null!=e.batchSize&&(a=e.batchSize),r.batchInputShape=[a,e.inputDim]}return r.units=e.units,Ca(r.units,"units"),r.activation=gc(e.activation),null!=e.useBias&&(r.useBias=e.useBias),r.kernelInitializer=Gi(e.kernelInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.biasInitializer=Gi(e.biasInitializer||r.DEFAULT_BIAS_INITIALIZER),r.kernelConstraint=Ba(e.kernelConstraint),r.biasConstraint=Ba(e.biasConstraint),r.kernelRegularizer=Sc(e.kernelRegularizer),r.biasRegularizer=Sc(e.biasRegularizer),r.activityRegularizer=Sc(e.activityRegularizer),r.supportsMasking=!0,r.inputSpec=[{minNDim:2}],r}return Object($r.a)(n,[{key:"build",value:function(e){var t=(e=Ji(e))[e.length-1];null==this.kernel&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:Object(Rc.a)({},-1,t)}],this.built=!0}},{key:"computeOutputShape",value:function(e){var t=(e=Ji(e)).slice();return t[t.length-1]=this.units,t}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t);var r,a=Zi(e),i=Ea(n.activation.getClassName());return null!=i?r=mi(a,n.kernel.read(),i,n.bias?n.bias.read():null):(r=mi(a,n.kernel.read()),null!=n.bias&&(r=Oi(r,n.bias.read())),null!=n.activation&&(r=n.activation.apply(r))),r}))}},{key:"getConfig",value:function(){var e={units:this.units,activation:mc(this.activation),useBias:this.useBias,kernelInitializer:Hi(this.kernelInitializer),biasInitializer:Hi(this.biasInitializer),kernelRegularizer:wc(this.kernelRegularizer),biasRegularizer:wc(this.biasRegularizer),activityRegularizer:wc(this.activityRegularizer),kernelConstraint:La(this.kernelConstraint),biasConstraint:La(this.biasConstraint)},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);vu.className="Dense",i.Se.registerClass(vu);var gu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),e=e||{},(r=t.call(this,e)).inputSpec=[{minNDim:3}],r.dataFormat=e.dataFormat,r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){e=Ji(e);var t,n=Object(ea.a)(e.slice(1));try{for(n.s();!(t=n.n()).done;){if(null==t.value)throw new ua('The shape of the input to "Flatten" is not fully defined '+"(got ".concat(e.slice(1),"). Make sure to pass a complete ")+'"input_shape" or "batch_input_shape" argument to the first layer in your model.')}}catch(r){n.e(r)}finally{n.f()}return[e[0],ni(e,1)]}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t);var r=Zi(e);if("channelsFirst"===n.dataFormat&&r.rank>1){for(var a=[0],o=2;o<r.rank;++o)a.push(o);a.push(1),r=Object(i.sf)(r,a)}return function(e){if(e.rank<=1)throw new ua("batchFlatten requires a minimum rank of 2. Got rank: ".concat(e.rank,"."));var t=[e.shape[0],ni(e.shape,1)];return i.Ne(e,t)}(r)}))}},{key:"getConfig",value:function(){var e={};null!=this.dataFormat&&(e.dataFormat=this.dataFormat);var t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);gu.className="Flatten",i.Se.registerClass(gu);var yu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).supportsMasking=!0,r.activation=gc(e.activation),r}return Object($r.a)(n,[{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t);var r=Zi(e);return n.activation.apply(r)}))}},{key:"getConfig",value:function(){var e={activation:mc(this.activation)},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);yu.className="Activation",i.Se.registerClass(yu);var Ou=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).n=e.n,r.inputSpec=[{ndim:2}],r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){return[e[0],this.n,e[1]]}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){return e=Zi(e),t=e,r=n.n,Object(i.pf)((function(){if(2!==t.shape.length)throw new ua("repeat() expects a rank-2 tensor, but received a "+"rank-".concat(t.shape.length," tensor."));return hi(si(t,1),[1,r,1])}));var t,r}))}},{key:"getConfig",value:function(){var e={n:this.n},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);Ou.className="RepeatVector",i.Se.registerClass(Ou);var xu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;Object(Yr.a)(this,n),(r=t.call(this,e)).targetShape=e.targetShape;for(var a=0;a<r.targetShape.length;++a)r.isUnknown(r.targetShape[a])&&(r.targetShape[a]=null);return r}return Object($r.a)(n,[{key:"isUnknown",value:function(e){return e<0||null==e}},{key:"fixUnknownDimension",value:function(e,t){for(var n="Total size of new array must be unchanged.",r=t.slice(),a=1,i=null,o=0;o<r.length;++o){var s=r[o];if(this.isUnknown(s)){if(null!==i)throw new ua("Can only specifiy one unknown dimension.");i=o}else a*=s}var c=ni(e);if(null!==i){if(0===a||c%a!==0)throw new ua(n);r[i]=c/a}else if(c!==a)throw new ua(n);return r}},{key:"computeOutputShape",value:function(e){for(var t=!1,n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t);var r=Zi(e),a=r.shape,o=a.slice(0,1).concat(n.fixUnknownDimension(a.slice(1),n.targetShape));return Object(i.Ne)(r,o)}))}},{key:"getConfig",value:function(){var e={targetShape:this.targetShape},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);xu.className="Reshape",i.Se.registerClass(xu);var ku=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),r=t.call(this,e),null==e.dims)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error("Permute constructor requires `dims` to be an Array, but received "+"".concat(e.dims," instead."));var a=ii(1,e.dims.length+1);if(!i.wf.arraysEqual(e.dims.slice().sort(),a))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");return r.dims=e.dims,r.dimsIncludingBatch=[0].concat(r.dims),r.inputSpec=[new io({ndim:r.dims.length+1})],r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){var t=(e=Ji(e)).slice();return this.dims.forEach((function(n,r){t[r+1]=e[n]})),t}},{key:"call",value:function(e,t){return Object(i.sf)(Zi(e),this.dimsIncludingBatch)}},{key:"getConfig",value:function(){var e={dims:this.dims},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);ku.className="Permute",i.Se.registerClass(ku);var wu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,null==e?{}:e)).supportsMasking=!0,r.maskValue=null!=e?null==e.maskValue?0:e.maskValue:0,r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){return e}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t={maskValue:this.maskValue};return Object.assign(t,e),t}},{key:"computeMask",value:function(e,t){var n=Zi(e);return Object(i.pd)(Object(i.Be)(n,this.maskValue),-1)}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t);var r=Zi(e),a=Object(i.pd)(Object(i.Be)(r,n.maskValue),-1,!0);return Object(i.ye)(r,Object(i.Ad)(a,r.dtype))}))}}]),n}(lo);wu.className="Masking",i.Se.registerClass(wu);var ju=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),(r=t.call(this,e)).embeddings=null,r.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",null==e.batchInputShape&&null==e.inputShape){var a=null;null!=e.batchSize&&(a=e.batchSize),null==e.inputLength?r.batchInputShape=[a,null]:r.batchInputShape=[a].concat(ma(e.inputLength))}return r.inputDim=e.inputDim,Ca(r.inputDim,"inputDim"),r.outputDim=e.outputDim,Ca(r.outputDim,"outputDim"),r.embeddingsInitializer=Gi(e.embeddingsInitializer||r.DEFAULT_EMBEDDINGS_INITIALIZER),r.embeddingsRegularizer=Sc(e.embeddingsRegularizer),r.activityRegularizer=Sc(e.activityRegularizer),r.embeddingsConstraint=Ba(e.embeddingsConstraint),r.maskZero=e.maskZero,r.supportsMasking=e.maskZero,r.inputLength=e.inputLength,r}return Object($r.a)(n,[{key:"build",value:function(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}},{key:"warnOnIncompatibleInputShape",value:function(e){}},{key:"computeMask",value:function(e,t){var n=this;return Object(i.pf)((function(){return n.maskZero?(e=Zi(e),Object(i.Be)(e,Object(i.Cf)(e))):null}))}},{key:"computeOutputShape",value:function(e){if(e=Ji(e),null==this.inputLength)return[].concat(Object(Vn.a)(e),[this.outputDim]);var t=ma(this.inputLength);if(t.length!==e.length-1)throw new ua('"inputLength" is '.concat(this.inputLength,", but received ")+"input shape has shape ".concat(e));for(var n=0,r=0;r<t.length;++r){var a=t[r],i=e[r+1];if(null!=a&&null!=i&&a!==i)throw new ua('"inputLength" is '.concat(this.inputLength,", but received ")+"input shape has shape ".concat(e));null==a&&(t[n]=i),n++}return[e[0]].concat(Object(Vn.a)(t),[this.outputDim])}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t);var r=Zi(e);"int32"!==r.dtype&&(r=oi(r,"int32"));var a=vi(n.embeddings.read(),Object(i.Ne)(r,[r.size]));return Object(i.Ne)(a,Ji(n.computeOutputShape(r.shape)))}))}},{key:"getConfig",value:function(){var e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Hi(this.embeddingsInitializer),embeddingsRegularizer:wc(this.embeddingsRegularizer),activityRegularizer:wc(this.activityRegularizer),embeddingsConstraint:La(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);ju.className="Embedding",i.Se.registerClass(ju);var Su=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e||{})).supportsMasking=!0,r}return Object($r.a)(n,[{key:"mergeFunction",value:function(e){throw new la}},{key:"computeElementwiseOpOutputShape",value:function(e,t){if(null==e||null==t)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(0===t.length)return e;for(var n=e.slice(0,e.length-t.length),r=0;r<t.length;++r){var a=e[e.length-t.length+r],i=t[r];if(null==a||null==i||a<0||i<0)n.push(null);else if(1===a)n.push(i);else if(1===i)n.push(a);else{if(a!==i)throw new ua("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}},{key:"build",value:function(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[Ji(e)]),(e=e).length<2)throw new ua("A merge layer should be called on an Array of at least 2 inputs."+" Got ".concat(e.length," input(s)."));var t,n=[],r=Object(ea.a)(e);try{for(r.s();!(t=r.n()).done;){var a=t.value;null!=a&&null!==a[0]&&n.push(a[0])}}catch(u){r.e(u)}finally{r.f()}if((n=ja(n)).length>1)throw new ua("Can not merge tensors with different batch sizes. "+"Got tensors with shapes: ".concat(JSON.stringify(e),"."));for(var i=null==e[0]?null:e[0].slice(1),o=1;o<e.length;++o){var s=null==e[o]?null:e[o].slice(1);i=this.computeElementwiseOpOutputShape(i,s)}var c=e.map((function(e){return e.length}));-1===e.indexOf(null)&&1===ja(c).length?this.reshapeRequired=!1:this.reshapeRequired=!0}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){if(e=e,n.reshapeRequired){var t=[],r=e.map((function(e){return e.rank}));if(-1===r.indexOf(null)){var a,o=ai(r),s=Object(ea.a)(e);try{for(s.s();!(a=s.n()).done;){for(var c=a.value,u=c.rank,l=0;l<o-u;++l)c=si(c,1);t.push(c)}}catch(I){s.e(I)}finally{s.f()}return n.mergeFunction(t)}var d,f=!1,p=Object(ea.a)(e);try{for(p.s();!(d=p.n()).done;){var h=d.value,b=h.rank;if(null==b){var m=h.shape,v=m[0],g=m.slice(1).concat([v]),y=i.Ne(h,[v].concat(ni(m.slice(1))));y=i.sf(y,[1,0]),y=i.Ne(y,g),t.push(y),f=!0}else if(b>1){var O=ii(1,b).concat([0]);t.push(i.sf(h,O)),f=!0}else t.push(h)}}catch(I){p.e(I)}finally{p.f()}var x=n.mergeFunction(t),k=x.rank;if(f)if(null==k){var w=x.shape,j=w[w.length-1],S=[j].concat(w.slice(0,w.length-1));x=i.Ne(i.sf(i.Ne(x,[-1,j]),[1,0]),S)}else if(k>1){var N=[k-1].concat(ii(0,k-1));x=i.sf(x,N)}return x}return n.mergeFunction(e)}))}},{key:"computeOutputShape",value:function(e){var t;t=null==(e=e)[0]?null:e[0].slice(1);for(var n=1;n<e.length;++n){var r=null==e[n]?null:e[n].slice(1);t=this.computeElementwiseOpOutputShape(t,r)}var a,i=[],o=Object(ea.a)(e);try{for(o.s();!(a=o.n()).done;){var s=a.value;null!=s&&null!==s[0]&&i.push(s[0])}}catch(c){o.e(c)}finally{o.f()}return t=1===(i=ja(i)).length?i.concat(t):[null].concat(t)}},{key:"computeMask",value:function(e,t){return i.pf((function(){if(null==t)return null;if(!Array.isArray(t))throw new ua("`mask` should be an Array");if(!Array.isArray(e))throw new ua("`inputs` should be an Array");if(t.length!==e.length)throw new ua("The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths "+"(".concat(e.length," vs ").concat(t.length,")"));if(t.every((function(e){return null==e})))return null;for(var n=(t=t.map((function(e){return null==e?e:i.Xd(e,0)})))[0],r=1;r<t.length-1;++r)n=i.oe(n,t[r]);return n}))}}]),n}(lo),Nu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"mergeFunction",value:function(e){return Object(i.pf)((function(){for(var t=e[0].clone(),n=1;n<e.length;++n)t=i.nd(t,e[n]);return t}))}}]),n}(Su);Nu.className="Add",i.Se.registerClass(Nu);var Iu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"mergeFunction",value:function(e){return Object(i.pf)((function(){for(var t=e[0].clone(),n=1;n<e.length;++n)t=i.ye(t,e[n]);return t}))}}]),n}(Su);Iu.className="Multiply",i.Se.registerClass(Iu);var Cu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"mergeFunction",value:function(e){return Object(i.pf)((function(){for(var t=e[0].clone(),n=1;n<e.length;++n)t=i.nd(t,e[n]);return i.ye(1/e.length,t)}))}}]),n}(Su);Cu.className="Average",i.Se.registerClass(Cu);var Tu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"mergeFunction",value:function(e){return Object(i.pf)((function(){for(var t=e[0],n=1;n<e.length;++n)t=i.te(t,e[n]);return t}))}}]),n}(Su);Tu.className="Maximum",i.Se.registerClass(Tu);var Eu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"mergeFunction",value:function(e){return Object(i.pf)((function(){for(var t=e[0],n=1;n<e.length;++n)t=i.we(t,e[n]);return t}))}}]),n}(Su);Eu.className="Minimum",i.Se.registerClass(Eu);var Au=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).DEFAULT_AXIS=-1,null==e&&(e={}),r.axis=null==e.axis?r.DEFAULT_AXIS:e.axis,r.supportsMasking=!0,r.reshapeRequired=!1,r}return Object($r.a)(n,[{key:"build",value:function(e){if(!Array.isArray(e)||!Array.isArray(e[0])||1===e.length)throw new ua("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;var t,n=!0,r=Object(ea.a)(e);try{for(r.s();!(t=r.n()).done;){if(null!=t.value){n=!1;break}}}catch(f){r.e(f)}finally{r.f()}if(!n){for(var a=[],o=0;o<e.length;++o){var s=e[o].slice();s.splice(this.axis,1);var c,u=!1,l=Object(ea.a)(a);try{for(l.s();!(c=l.n()).done;){var d=c.value;if(i.wf.arraysEqual(d,s)){u=!0;break}}}catch(f){l.e(f)}finally{l.f()}u||a.push(s)}if(a.length>1)throw new ua("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}}},{key:"mergeFunction",value:function(e){var t=this;return Object(i.pf)((function(){return fi(e,t.axis)}))}},{key:"computeOutputShape",value:function(e){if(!Array.isArray(e)||!Array.isArray(e[0]))throw new ua("A `Concatenate` layer should be called on a list of inputs.");var t,n=e,r=n[0].slice(),a=this.axis<0?r.length+this.axis:this.axis,i=Object(ea.a)(n.slice(1));try{for(i.s();!(t=i.n()).done;){var o=t.value;if(null==r[a]||null==o[a]){r[a]=null;break}r[a]+=o[a]}}catch(s){i.e(s)}finally{i.f()}return r}},{key:"computeMask",value:function(e,t){var n=this;if(null==t)return null;if(!Array.isArray(t))throw new ua("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new ua("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new ua("Mismatch in the length of mask (".concat(t.length,") ")+"and the legnth of inputs (".concat(e.length,")"));return i.pf((function(){var r=!0;if(t.forEach((function(e){null==e||(r=!1)})),r)return null;for(var a=[],o=0;o<e.length;++o)null==t[o]?a.push(i.Ad(i.Ee(e[o]),"bool")):t[o].rank<e[o].rank?a.push(i.Xd(t[o],-1)):a.push(t[o]);var s=i.Dd(a,n.axis);return i.od(s,-1,!1)}))}},{key:"getConfig",value:function(){var e={axis:this.axis},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(Su);function Ru(e,t){for(;e<0;)e+=t;return e}Au.className="Concatenate",i.Se.registerClass(Au);var Fu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).axes=e.axes,r.normalize=null!=e.normalize&&e.normalize,r.supportsMasking=!0,r.reshapeRequired=!1,r}return Object($r.a)(n,[{key:"build",value:function(e){i.wf.assert(Array.isArray(e)&&2===e.length&&Array.isArray(e[0])&&Array.isArray(e[1]),(function(){return"A `Dot` layer should be called on a list of exactly 2 inputs."}));var t=e[0],n=e[1];if(t.length>3||n.length>3)throw new la("Dot layer does not support tensors of 4D or higher rank yet.");var r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new ua("Dimension incompatibility: "+"".concat(t[r[0]]," !== ").concat(n[r[1]]))}},{key:"mergeFunction",value:function(e){if(2!==e.length)throw new ua("A `Dot` layer must be called on exactly 2 inputs, "+"but received ".concat(e.length," input(s)."));var t,n=e[0],r=e[1];return t=Array.isArray(this.axes)?this.axes.map((function(t,n){return Ru(t,e[n].shape.length)})):[Ru(this.axes,n.shape.length),Ru(this.axes,r.shape.length)],this.normalize&&(n=Ro(n,t[0]),r=Ro(r,t[1])),function(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new la("batchDot is not implemented for tensors of 4D or higher rank yet");if(i.wf.assert(e.shape.length>=2,(function(){return"batchDot requires the rank of x to be >= 2, "+"but got ".concat(e.shape.length)})),i.wf.assert(e.shape.length>=2,(function(){return"batchDot requires the rank of y to be >= 2, "+"but got ".concat(t.shape.length)})),"number"===typeof n&&(n=[n,n]),"complex64"===e.dtype||"complex64"===t.dtype)throw new la("batchDot is not implemented for complex64-type Tensors yet.");var r=e.shape.length,a=t.shape.length;null==n&&(n=[r-1,a-2]);var o=n;return i.pf((function(){var n,s;if(r>a){n=r-a;for(var c=[],u=0;u<n;++u)c.push(1);t=i.Ne(t,t.shape.concat(c))}else if(a>r){n=a-r;for(var l=[],d=0;d<n;++d)l.push(1);e=i.Ne(e,e.shape.concat(l))}else n=0;if(2===e.shape.length&&2===t.shape.length)s=o[0]===o[1]?i.if(i.ye(e,t),o[0]):i.if(i.ye(i.sf(e,[1,0]),t),o[1]);else{var f=o[0]!==e.shape.length-1,p=o[1]===t.shape.length-1;s=i.pe(e,t,f,p)}if(n>0){for(var h,b=[],m=h=r>a?r+a-3:r-1;m<h+n;++m)b.push(m);s=i.ff(s,b)}return 1===s.shape.length&&(s=i.Xd(s,1)),s}))}(n,r,t)}},{key:"interpretAxes",value:function(e,t){return Array.isArray(this.axes)?this.axes:[Ru(this.axes,e.length),Ru(this.axes,t.length)]}},{key:"computeOutputShape",value:function(e){i.wf.assert(Array.isArray(e)&&2===e.length&&Array.isArray(e[0])&&Array.isArray(e[1]),(function(){return"A `Dot` layer should be called on a list of exactly 2 inputs."}));var t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new la("Dot layer does not support tensors of 4D or higher rank yet.");var r=this.interpretAxes(t,n);t.splice(r[0],1),n.splice(r[1],1),n.splice(0,1);var a=t.concat(n);return 1===a.length&&a.push(1),a}},{key:"computeMask",value:function(e,t){return null}},{key:"getConfig",value:function(){var e={axes:this.axes,normalize:this.normalize},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(Su);Fu.className="Dot",i.Se.registerClass(Fu);var Du=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).supportsMasking=!0,r.stddev=e.stddev,r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){return e}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t={stddev:this.stddev};return Object.assign(t,e),t}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t);var r=Zi(e);return wi((function(){return Object(i.nd)(bi(r.shape,0,n.stddev),r)}),(function(){return r}),t.training||!1)}))}}]),n}(lo);Du.className="GaussianNoise",i.Se.registerClass(Du);var _u=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).supportsMasking=!0,r.rate=e.rate,r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){return e}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t={rate:this.rate};return Object.assign(t,e),t}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t);var r=Zi(e);if(n.rate>0&&n.rate<1){return wi((function(){var e=Math.sqrt(n.rate/(1-n.rate));return Object(i.ye)(r,bi(r.shape,1,e))}),(function(){return r}),t.training||!1)}return r}))}}]),n}(lo);_u.className="GaussianDropout",i.Se.registerClass(_u);var Mu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).supportsMasking=!0,r.rate=e.rate,r.noiseShape=e.noiseShape,r}return Object($r.a)(n,[{key:"_getNoiseShape",value:function(e){return this.noiseShape||Zi(e).shape}},{key:"computeOutputShape",value:function(e){return e}},{key:"getConfig",value:function(){var e=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this),t={rate:this.rate};return Object.assign(t,e),t}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){if(n.rate<1&&n.rate>0){var r=n._getNoiseShape(e);return wi((function(){var t=Zi(e),a=-1.7580993408473766,o=Object(i.ee)(Object(i.Je)(r),n.rate);o=oi(o,"float32");var s=Math.pow((1-n.rate)*(1+n.rate*Math.pow(a,2)),-.5),c=-s*a*n.rate,u=Object(i.nd)(Object(i.ye)(t,o),Object(i.ye)(Object(i.nd)(o,-1),a));return Object(i.nd)(Object(i.ye)(u,s),c)}),(function(){return Zi(e)}),t.training||!1)}return e}))}}]),n}(lo);function zu(e,t,n,r,a){var o,s=arguments.length>5&&void 0!==arguments[5]?arguments[5]:.001;if(2===e.rank)o=i.vd(e,t,n,r,a,s);else if(3===e.rank)o=i.wd(e,t,n,r,a,s);else{if(4!==e.rank)throw new la("batchNormalization is not implemented for array of rank ".concat(e.rank," ")+"yet");o=i.xd(e,t,n,r,a,s)}return o}function Lu(e,t,n,r){var a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:.001;return Object(i.pf)((function(){var o=i.xe(e,r),s=o.mean,c=o.variance;return[zu(e,s,c,n,t,a),s,c]}))}function Pu(e,t,n,r){var a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:.001;return Object(i.pf)((function(){var o,s=i.xe(e,r),c=s.mean,u=s.variance,l=[],d=Object(ea.a)(ii(0,e.rank));try{for(d.s();!(o=d.n()).done;){var f=o.value;-1!==r.indexOf(f)?l.push(1):l.push(e.shape[f])}}catch(v){d.e(v)}finally{d.f()}var p=Object(i.Ne)(c,l),h=Object(i.Ne)(u,l),b=null==t?null:Object(i.Ne)(t,l),m=null==n?null:Object(i.Ne)(n,l);return[zu(e,p,h,m,b,a),c,u]}))}Mu.className="AlphaDropout",i.Se.registerClass(Mu);var Bu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),null==e&&(e={}),(r=t.call(this,e)).supportsMasking=!0,r.axis=null==e.axis?-1:e.axis,r.momentum=null==e.momentum?.99:e.momentum,r.epsilon=null==e.epsilon?.001:e.epsilon,r.center=null==e.center||e.center,r.scale=null==e.scale||e.scale,r.betaInitializer=Gi(e.betaInitializer||"zeros"),r.gammaInitializer=Gi(e.gammaInitializer||"ones"),r.movingMeanInitializer=Gi(e.movingMeanInitializer||"zeros"),r.movingVarianceInitializer=Gi(e.movingVarianceInitializer||"ones"),r.betaConstraint=Ba(e.betaConstraint),r.gammaConstraint=Ba(e.gammaConstraint),r.betaRegularizer=Sc(e.betaRegularizer),r.gammaRegularizer=Sc(e.gammaRegularizer),r}return Object($r.a)(n,[{key:"build",value:function(e){e=Ji(e);var t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(null==n)throw new ua("Axis ".concat(t," of input tensor should have a defined dimension but ")+"the layer received an input with shape "+"".concat(JSON.stringify(e),"."));this.inputSpec=[new io({ndim:e.length,axes:Object(Rc.a)({},t,n)})];var r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var r=null!=t.training&&t.training,a=Zi(e),s=a.shape,c=s.length,u=ii(0,c),l=n.axis>=0?n.axis:n.axis+c;u.splice(l,1);var d=fa(1,c);d[l]=s[l];var f=u.slice();f.sort();var p=!i.wf.arraysEqual(f,ii(0,c).slice(0,c-1));if(!r)return function(){if(p){var e=Object(i.Ne)(n.movingMean.read(),d),t=Object(i.Ne)(n.movingVariance.read(),d),r=n.center?Object(i.Ne)(n.beta.read(),d):null,o=n.scale?Object(i.Ne)(n.gamma.read(),d):null;return zu(a,e,t,r,o,n.epsilon)}return zu(a,n.movingMean.read(),n.movingVariance.read(),null==n.beta?null:n.beta.read(),null==n.gamma?null:n.gamma.read(),n.epsilon)}();var h=function(e,t,n,r){var a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:.001;return i.wf.arraysEqual(r.slice().sort(),ii(0,e.rank-1))?Lu(e,t,n,r,a):Pu(e,t,n,r,a)}(a,n.gamma.read(),n.beta.read(),u,n.epsilon),b=Object(o.a)(h,3),m=b[0],v=b[1],g=b[2],y=function(e,t,n){i.pf((function(){var r=1-n,a=e.read(),o=i.ye(i.hf(a,t),r);e.write(i.hf(a,o))}))};return y(n.movingMean,v,n.momentum),y(n.movingVariance,g,n.momentum),m}))}},{key:"getConfig",value:function(){var e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Hi(this.betaInitializer),gammaInitializer:Hi(this.gammaInitializer),movingMeanInitializer:Hi(this.movingMeanInitializer),movingVarianceInitializer:Hi(this.movingVarianceInitializer),betaRegularizer:wc(this.betaRegularizer),gammaRegularizer:wc(this.gammaRegularizer),betaConstraint:La(this.betaConstraint),gammaConstraint:La(this.gammaConstraint)},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);Bu.className="BatchNormalization",i.Se.registerClass(Bu);var Wu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),null==e&&(e={}),(r=t.call(this,e)).axis=null==e.axis?-1:e.axis,"number"===typeof r.axis){if(!Number.isInteger(r.axis))throw new Error("Expected axis to be an integer, but received ".concat(r.axis))}else{if(!Array.isArray(r.axis))throw new Error("Expected axis to be an integer or an array of integers, "+"but received ".concat(JSON.stringify(r.axis)));var a,i=Object(ea.a)(r.axis);try{for(i.s();!(a=i.n()).done;){var o=a.value;if(!Number.isInteger(o))throw new Error("Expected axis to be an array of integers, "+"but received ".concat(JSON.stringify(r.axis)))}}catch(s){i.e(s)}finally{i.f()}}return r.epsilon=null==e.epsilon?.001:e.epsilon,r.center=null==e.center||e.center,r.scale=null==e.scale||e.scale,r.betaInitializer=Gi(e.betaInitializer||"zeros"),r.gammaInitializer=Gi(e.gammaInitializer||"ones"),r.betaRegularizer=Sc(e.betaRegularizer),r.gammaRegularizer=Sc(e.gammaRegularizer),r.supportsMasking=!0,r}return Object($r.a)(n,[{key:"build",value:function(e){var t=(e=Ji(e)).length;"number"===typeof this.axis&&(this.axis=[this.axis]);for(var n=0;n<this.axis.length;++n)this.axis[n]<0&&(this.axis[n]+=t);var r,a=Object(ea.a)(this.axis);try{for(a.s();!(r=a.n()).done;){var i=r.value;if(i<0||i>=t)throw new Error("Invalid axis: ".concat(i))}}catch(s){a.e(s)}finally{a.f()}if(this.axis.length!==ja(this.axis).length)throw new Error("Found duplicate axes in: ".concat(this.axis));var o=this.axis.map((function(t){return e[t]}));this.scale?this.gamma=this.addWeight("gamma",o,"float32",this.gammaInitializer,this.gammaRegularizer,true):this.gamma=null,this.center?this.beta=this.addWeight("beta",o,"float32",this.betaInitializer,this.betaRegularizer,true):this.beta=null,this.built=!0}},{key:"call",value:function(e,t){var n=this,r=Zi(e),a=r.shape,o=a.length;return Object(i.pf)((function(){var e,t=Object(i.xe)(r,n.axis,!0),s=t.mean,c=t.variance,u=fa(1,o),l=Object(ea.a)(n.axis);try{for(l.s();!(e=l.n()).done;){var d=e.value;u[d]=a[d]}}catch(g){l.e(g)}finally{l.f()}for(var f=function(e){return null!=e&&e.shape.length!==o&&n.axis!==[o-1]?i.Ne(e,u):e},p=f(n.gamma.read()),h=f(n.beta.read()),b=[],m=[],v=0;v<o;++v)-1!==n.axis.indexOf(v)?(b.push(a[v]),m.push(1)):(b.push(1),m.push(a[v]));return s=i.qf(s,b),c=i.qf(c,b),p=i.qf(p,m),h=i.qf(h,m),zu(r,s,c,h,p,n.epsilon)}))}},{key:"getConfig",value:function(){var e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Hi(this.betaInitializer),gammaInitializer:Hi(this.gammaInitializer),betaRegularizer:wc(this.betaRegularizer),gammaRegularizer:wc(this.gammaRegularizer)},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);Wu.className="LayerNormalization",i.Se.registerClass(Wu);var Uu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),null==e&&(e={}),(r=t.call(this,e)).dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,null==e.padding)r.padding=[[1,1],[1,1]];else if("number"===typeof e.padding)r.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,2!==e.padding.length)throw new ua("ZeroPadding2D expects padding to be a length-2 array, but "+"received a length-".concat(e.padding.length," array."));var a,i;if("number"===typeof e.padding[0])a=[e.padding[0],e.padding[0]],i=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,2!==e.padding[0].length)throw new ua("ZeroPadding2D expects height padding to be a length-2 array, "+"but received a length-".concat(e.padding[0].length," array."));if(a=e.padding[0],2!==e.padding[1].length)throw new ua("ZeroPadding2D expects width padding to be a length-2 array, "+"but received a length-".concat(e.padding[1].length," array."));i=e.padding[1]}r.padding=[a,i]}return r.inputSpec=[new io({ndim:4})],r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){var t,n;return e=Ji(e),"channelsFirst"===this.dataFormat?(t=null!=e[2]&&e[2]>=0?e[2]+this.padding[0][0]+this.padding[0][1]:null,n=null!=e[3]&&e[3]>=0?e[3]+this.padding[1][0]+this.padding[1][1]:null,[e[0],e[1],t,n]):(t=null!=e[1]&&e[1]>=0?e[1]+this.padding[0][0]+this.padding[0][1]:null,n=null!=e[2]&&e[2]>=0?e[2]+this.padding[1][0]+this.padding[1][1]:null,[e[0],t,n,e[3]])}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){return t=Zi(e),r=n.padding,a=n.dataFormat,Object(i.pf)((function(){if(4!==t.rank)throw new ua("temporalPadding expects input tensor to be 4-D, but received a "+"".concat(t.rank,"-D tensor."));if(null==r&&(r=[[1,1],[1,1]]),2!==r.length||2!==r[0].length||2!==r[1].length)throw new ua("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(null==a&&(a="channelsLast"),"channelsLast"!==a&&"channelsFirst"!==a)throw new ua("Unknown data format: ".concat(a,". ")+"Supported data formats are 'channelsLast' and 'channelsFirst.");var e;return e="channelsFirst"===a?[[0,0],[0,0],r[0],r[1]]:[[0,0],r[0],r[1],[0,0]],i.Fe(t,e)}));var t,r,a}))}},{key:"getConfig",value:function(){var e={padding:this.padding,dataFormat:this.dataFormat},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo);function Vu(e,t,n,r,a,o){return Object(i.pf)((function(){var s;Ka(a),Ya(o),Xa(r),null==n&&(n=[1,1]),null==r&&(r="valid"),null==a&&(a="channelsLast"),null==o&&(o="max"),e=Mc(e,a);var c="same"===r?"same":"valid";return s="max"===o?i.re(e,t,n,c):i.rd(e,t,n,c),"channelsFirst"===a&&(s=i.sf(s,[0,3,1,2])),s}))}function Hu(e,t,n,r,a,o){return Object(i.pf)((function(){var s;Ka(a),Ya(o),Xa(r),null==n&&(n=[1,1,1]),null==r&&(r="valid"),null==a&&(a="channelsLast"),null==o&&(o="max"),e=zc(e,a);var c="same"===r?"same":"valid";return s="max"===o?i.se(e,t,n,c):i.sd(e,t,n,c),"channelsFirst"===a&&(s=i.sf(s,[0,4,1,2,3])),s}))}Uu.className="ZeroPadding2D",i.Se.registerClass(Uu);var Gu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),null==e.poolSize&&(e.poolSize=2),r=t.call(this,e),"number"===typeof e.poolSize)r.poolSize=[e.poolSize];else{if(!Array.isArray(e.poolSize)||1!==e.poolSize.length||"number"!==typeof e.poolSize[0])throw new ua("poolSize for 1D convolutional layer must be a number or an Array of a single number, but received "+"".concat(JSON.stringify(e.poolSize)));r.poolSize=e.poolSize}if(Ca(r.poolSize,"poolSize"),null==e.strides)r.strides=r.poolSize;else if("number"===typeof e.strides)r.strides=[e.strides];else{if(!Array.isArray(e.strides)||1!==e.strides.length||"number"!==typeof e.strides[0])throw new ua("strides for 1D convolutional layer must be a number or an Array of a single number, but received "+"".concat(JSON.stringify(e.strides)));r.strides=e.strides}return Ca(r.strides,"strides"),r.padding=null==e.padding?"valid":e.padding,Xa(r.padding),r.inputSpec=[new io({ndim:3})],r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){var t=Dc((e=Ji(e))[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){n.invokeCallHook(e,t),e=si(Zi(e),2);var r=n.poolingFunction(Zi(e),[n.poolSize[0],1],[n.strides[0],1],n.padding,"channelsLast");return i.ff(r,[2])}))}},{key:"getConfig",value:function(){var e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo),qu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"poolingFunction",value:function(e,t,n,r,a){return Ka(a),Xa(r),Vu(e,t,n,r,a,"max")}}]),n}(Gu);qu.className="MaxPooling1D",i.Se.registerClass(qu);var Ku=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"poolingFunction",value:function(e,t,n,r,a){return Ka(a),Xa(r),Vu(e,t,n,r,a,"avg")}}]),n}(Gu);Ku.className="AveragePooling1D",i.Se.registerClass(Ku);var Xu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),null==e.poolSize&&(e.poolSize=[2,2]),(r=t.call(this,e)).poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],null==e.strides)r.strides=r.poolSize;else if(Array.isArray(e.strides)){if(2!==e.strides.length)throw new ua("If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length "+"".concat(e.strides.length,"."));r.strides=e.strides}else r.strides=[e.strides,e.strides];return Ca(r.poolSize,"poolSize"),Ca(r.strides,"strides"),r.padding=null==e.padding?"valid":e.padding,r.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,Ka(r.dataFormat),Xa(r.padding),r.inputSpec=[new io({ndim:4})],r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){e=Ji(e);var t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2];return t=Dc(t,this.poolSize[0],this.padding,this.strides[0]),n=Dc(n,this.poolSize[1],this.padding,this.strides[1]),"channelsFirst"===this.dataFormat?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){return n.invokeCallHook(e,t),n.poolingFunction(Zi(e),n.poolSize,n.strides,n.padding,n.dataFormat)}))}},{key:"getConfig",value:function(){var e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo),Yu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"poolingFunction",value:function(e,t,n,r,a){return Ka(a),Xa(r),Vu(e,t,n,r,a,"max")}}]),n}(Xu);Yu.className="MaxPooling2D",i.Se.registerClass(Yu);var $u=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"poolingFunction",value:function(e,t,n,r,a){return Ka(a),Xa(r),Vu(e,t,n,r,a,"avg")}}]),n}(Xu);$u.className="AveragePooling2D",i.Se.registerClass($u);var Qu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;if(Object(Yr.a)(this,n),null==e.poolSize&&(e.poolSize=[2,2,2]),(r=t.call(this,e)).poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],null==e.strides)r.strides=r.poolSize;else if(Array.isArray(e.strides)){if(3!==e.strides.length)throw new ua("If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length "+"".concat(e.strides.length,"."));r.strides=e.strides}else r.strides=[e.strides,e.strides,e.strides];return Ca(r.poolSize,"poolSize"),Ca(r.strides,"strides"),r.padding=null==e.padding?"valid":e.padding,r.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,Ka(r.dataFormat),Xa(r.padding),r.inputSpec=[new io({ndim:5})],r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){e=Ji(e);var t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2],r="channelsFirst"===this.dataFormat?e[4]:e[3];return t=Dc(t,this.poolSize[0],this.padding,this.strides[0]),n=Dc(n,this.poolSize[1],this.padding,this.strides[1]),r=Dc(r,this.poolSize[2],this.padding,this.strides[2]),"channelsFirst"===this.dataFormat?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){return n.invokeCallHook(e,t),n.poolingFunction(Zi(e),n.poolSize,n.strides,n.padding,n.dataFormat)}))}},{key:"getConfig",value:function(){var e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo),Zu=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"poolingFunction",value:function(e,t,n,r,a){return Ka(a),Xa(r),Hu(e,t,n,r,a,"max")}}]),n}(Qu);Zu.className="MaxPooling3D",i.Se.registerClass(Zu);var Ju=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e)}return Object($r.a)(n,[{key:"poolingFunction",value:function(e,t,n,r,a){return Ka(a),Xa(r),Hu(e,t,n,r,a,"avg")}}]),n}(Qu);Ju.className="AveragePooling3D",i.Se.registerClass(Ju);var el=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).inputSpec=[new io({ndim:3})],r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){return[e[0],e[2]]}},{key:"call",value:function(e,t){throw new la}}]),n}(lo),tl=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e||{})}return Object($r.a)(n,[{key:"call",value:function(e,t){return Object(i.pf)((function(){var t=Zi(e);return i.ue(t,1)}))}}]),n}(el);tl.className="GlobalAveragePooling1D",i.Se.registerClass(tl);var nl=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){return Object(Yr.a)(this,n),t.call(this,e||{})}return Object($r.a)(n,[{key:"call",value:function(e,t){return Object(i.pf)((function(){var t=Zi(e);return i.qe(t,1)}))}}]),n}(el);nl.className="GlobalMaxPooling1D",i.Se.registerClass(nl);var rl=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,Ka(r.dataFormat),r.inputSpec=[new io({ndim:4})],r}return Object($r.a)(n,[{key:"computeOutputShape",value:function(e){return e=e,"channelsLast"===this.dataFormat?[e[0],e[3]]:[e[0],e[1]]}},{key:"call",value:function(e,t){throw new la}},{key:"getConfig",value:function(){var e={dataFormat:this.dataFormat},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}]),n}(lo),al=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(){return Object(Yr.a)(this,n),t.apply(this,arguments)}return Object($r.a)(n,[{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var t=Zi(e);return"channelsLast"===n.dataFormat?i.ue(t,[1,2]):i.ue(t,[2,3])}))}}]),n}(rl);al.className="GlobalAveragePooling2D",i.Se.registerClass(al);var il=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(){return Object(Yr.a)(this,n),t.apply(this,arguments)}return Object($r.a)(n,[{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var t=Zi(e);return"channelsLast"===n.dataFormat?i.qe(t,[1,2]):i.qe(t,[2,3])}))}}]),n}(rl);il.className="GlobalMaxPooling2D",i.Se.registerClass(il);var ol=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).layer=e.layer,r}return Object($r.a)(n,[{key:"build",value:function(e){this.built=!0}},{key:"trainable",get:function(){return null!=this.layer&&this.layer.trainable},set:function(e){null!=this.layer&&(this.layer.trainable=e)}},{key:"trainableWeights",get:function(){return this.layer.trainableWeights}},{key:"nonTrainableWeights",get:function(){return this.layer.nonTrainableWeights}},{key:"updates",get:function(){return this.layer._updates}},{key:"losses",get:function(){return this.layer.losses}},{key:"getWeights",value:function(){return this.layer.getWeights()}},{key:"setWeights",value:function(e){this.layer.setWeights(e)}},{key:"getConfig",value:function(){var e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}},{key:"setFastWeightInitDuringBuild",value:function(e){Object(Eo.a)(Object(na.a)(n.prototype),"setFastWeightInitDuringBuild",this).call(this,e),null!=this.layer&&this.layer.setFastWeightInitDuringBuild(e)}}],[{key:"fromConfig",value:function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{},r=t.layer,a=Ao(r,n);delete t.layer;var i={layer:a};return Object.assign(i,t),new e(i)}}]),n}(lo),sl=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;return Object(Yr.a)(this,n),(r=t.call(this,e)).supportsMasking=!0,r}return Object($r.a)(n,[{key:"build",value:function(e){if((e=Ji(e)).length<3)throw new ua("TimeDistributed layer expects an input shape >= 3D, but received "+"input shape ".concat(JSON.stringify(e)));this.inputSpec=[{shape:e}];var t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),Object(Eo.a)(Object(na.a)(n.prototype),"build",this).call(this,e)}},{key:"computeOutputShape",value:function(e){var t=[(e=Ji(e))[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){return eu((function(e,r){return[Zi(n.layer.call(e,t)),[]]}),e=Zi(e),[],!1,null,null,!1,!0)[1]}))}}]),n}(ol);sl.className="TimeDistributed",i.Se.registerClass(sl);var cl=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r;Object(Yr.a)(this,n),r=t.call(this,e);var a=e.layer.getConfig(),i={};i.className=e.layer.getClassName(),i.config=a,r.forwardLayer=Ao(i),a.goBackwards=!0!==a.goBackwards;var o,s={};if(s.className=e.layer.getClassName(),s.config=a,r.backwardLayer=Ao(s),r.forwardLayer.name="forward_"+r.forwardLayer.name,r.backwardLayer.name="backward_"+r.backwardLayer.name,r.mergeMode=void 0===e.mergeMode?"concat":e.mergeMode,o=r.mergeMode,Na(Ga,"BidirectionalMergeMode",o),e.weights)throw new la("weights support is not implemented for Bidirectional layer yet.");return r._stateful=e.layer.stateful,r.returnSequences=e.layer.returnSequences,r.returnState=e.layer.returnState,r.supportsMasking=!0,r._trainable=!0,r.inputSpec=e.layer.inputSpec,r.numConstants=null,r}return Object($r.a)(n,[{key:"trainable",get:function(){return this._trainable},set:function(e){this._trainable=e,null!=this.forwardLayer&&(this.forwardLayer.trainable=e),null!=this.backwardLayer&&(this.backwardLayer.trainable=e)}},{key:"getWeights",value:function(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}},{key:"setWeights",value:function(e){var t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}},{key:"computeOutputShape",value:function(e){var t,n,r,a=this.forwardLayer.computeOutputShape(e);return Array.isArray(a)&&Array.isArray(a[0])||(a=[a]),a=a,this.returnState?(r=a.slice(1),t=a[0]):t=a[0],t=t,"concat"===this.mergeMode?(t[t.length-1]*=2,n=[t]):n=null==this.mergeMode?[t,t.slice()]:[t],this.returnState?null==this.mergeMode?n.concat(r).concat(r.slice()):[t].concat(r).concat(r.slice()):ba(n)}},{key:"apply",value:function(e,t){var r=null==t?null:t.initialState,a=null==t?null:t.constants;null==t&&(t={});var i=Jc(e,r,a,this.numConstants);if(e=i.inputs,r=i.initialState,a=i.constants,Array.isArray(e)&&(r=e.slice(1),e=e[0]),(null==r||0===r.length)&&null==a)return Object(Eo.a)(Object(na.a)(n.prototype),"apply",this).call(this,e,t);var o=[],s=[];if(null!=r){var c=r.length;if(c%2>0)throw new ua("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=r,o.push.apply(o,Object(Vn.a)(r));var u=r.map((function(e){return new io({shape:e.shape})}));this.forwardLayer.stateSpec=u.slice(0,c/2),this.backwardLayer.stateSpec=u.slice(c/2),s.push.apply(s,Object(Vn.a)(u))}if(null!=a)throw new la("Support for constants in Bidirectional layers is not implemented yet.");for(var l=o[0]instanceof oo,d=0,f=o;d<f.length;d++){if(f[d]instanceof oo!==l)throw new ua("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors")}if(l){var p=[e].concat(o),h=this.inputSpec.concat(s),b=this.inputSpec;this.inputSpec=h;var m=Object(Eo.a)(Object(na.a)(n.prototype),"apply",this).call(this,p,t);return this.inputSpec=b,m}return Object(Eo.a)(Object(na.a)(n.prototype),"apply",this).call(this,e,t)}},{key:"call",value:function(e,t){var n=this;return Object(i.pf)((function(){var r,a,o,s,c=t.initialState;if(null==c)r=n.forwardLayer.call(e,t),a=n.backwardLayer.call(e,t);else{var u=c.slice(0,c.length/2),l=c.slice(c.length/2);r=n.forwardLayer.call(e,Object.assign(t,{initialState:u})),a=n.backwardLayer.call(e,Object.assign(t,{initialState:l}))}return n.returnState&&(Array.isArray(r)&&(o=r.slice(1).concat(a.slice(1))),r=r[0],a=a[0]),n.returnSequences&&(a=i.Oe(a,1)),"concat"===n.mergeMode?s=fi([r,a]):"sum"===n.mergeMode?s=i.nd(r,a):"ave"===n.mergeMode?s=i.ye(.5,i.nd(r,a)):"mul"===n.mergeMode?s=i.ye(r,a):null==n.mergeMode&&(s=[r,a]),n.returnState?null==n.mergeMode?s.concat(o):[s].concat(o):s}))}},{key:"resetStates",value:function(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}},{key:"build",value:function(e){var t=this;Qa(this.forwardLayer.name,(function(){t.forwardLayer.build(e)})),Qa(this.backwardLayer.name,(function(){t.backwardLayer.build(e)})),this.built=!0}},{key:"computeMask",value:function(e,t){var n;if(Array.isArray(t)&&(t=t[0]),n=this.returnSequences?null==this.mergeMode?[t,t]:t:null==this.mergeMode?[null,null]:null,this.returnState){var r=this.forwardLayer.states.map((function(e){return null}));return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}return n}},{key:"trainableWeights",get:function(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}},{key:"nonTrainableWeights",get:function(){return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights)}},{key:"setFastWeightInitDuringBuild",value:function(e){Object(Eo.a)(Object(na.a)(n.prototype),"setFastWeightInitDuringBuild",this).call(this,e),null!=this.forwardLayer&&this.forwardLayer.setFastWeightInitDuringBuild(e),null!=this.backwardLayer&&this.backwardLayer.setFastWeightInitDuringBuild(e)}},{key:"getConfig",value:function(){var e={mergeMode:this.mergeMode},t=Object(Eo.a)(Object(na.a)(n.prototype),"getConfig",this).call(this);return Object.assign(e,t),e}}],[{key:"fromConfig",value:function(e,t){var n=Ao(t.layer);if(delete t.layer,null!=t.numConstants)throw new la("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");var r=t;return r.layer=n,new e(r)}}]),n}(ol);cl.className="Bidirectional",i.Se.registerClass(cl);var ul=n(80),ll=n(1),dl=function(){function e(t,n,r){var a=this;Object(Yr.a)(this,e),this.node=t,this.tensorMap=n,this.context=r,this.inputs=[],this.attrs={},this.inputs=t.inputNames.map((function(e){return a.getInput(e)})),null!=t.rawAttrs&&(this.attrs=Object.keys(t.rawAttrs).reduce((function(e,t){return e[t]=a.getAttr(t),e}),{}))}return Object($r.a)(e,[{key:"getInput",value:function(e){return Object(ll.e)(e,this.tensorMap,this.context)}},{key:"getAttr",value:function(e,t){var n=this.node.rawAttrs[e];if(null!=n.tensor)return Object(ll.e)(e,this.tensorMap,this.context);if(null!=n.i||null!=n.f)return Object(ul.f)(this.node.rawAttrs,e,t);if(null!=n.s)return Object(ul.i)(this.node.rawAttrs,e,t);if(null!=n.b)return Object(ul.c)(this.node.rawAttrs,e,t);if(null!=n.shape)return Object(ul.k)(this.node.rawAttrs,e,t);if(null!=n.type)return Object(ul.e)(this.node.rawAttrs,e,t);if(null!=n.list){if(null!=n.list.i||null!=n.list.f)return Object(ul.g)(this.node.rawAttrs,e,t);if(null!=n.list.s)return Object(ul.h)(this.node.rawAttrs,e,t);if(null!=n.list.shape)return Object(ul.j)(this.node.rawAttrs,e,t);if(null!=n.list.b)return Object(ul.b)(this.node.rawAttrs,e,t);if(null!=n.list.type)return Object(ul.d)(this.node.rawAttrs,e,t)}return t}}]),e}(),fl=n(131),pl=n(251),hl=n(81),bl=n(149),ml=n(133);function vl(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:"";if("number"!==typeof e&&"number"!==typeof t){i.wf.assert(e.length===t.length,(function(){return n+" Shapes ".concat(e," and ").concat(t," must match")}));for(var r=0;r<e.length;r++){var a=e[r],o=t[r];i.wf.assert(a<0||o<0||a===o,(function(){return n+" Shapes ".concat(e," and ").concat(t," must match")}))}}}function gl(e){return"number"!==typeof e&&!e.some((function(e){return e<0}))}function yl(e,t,n){var r=Ol(e,n),a=!gl(r);if(a&&0===t.length)throw new Error("Tried to calculate elements of an empty list"+" with non-fully-defined elementShape: ".concat(r));if(a&&t.forEach((function(e){r=Ol(e.shape,r)})),!gl(r))throw new Error("Non-fully-defined elementShape: ".concat(r));return r}function Ol(e,t){if("number"===typeof e)return t;if("number"===typeof t)return e;if(e.length!==t.length)throw new Error("Incompatible ranks during merge: ".concat(e," vs. ").concat(t));for(var n=[],r=0;r<e.length;++r){var a=e[r],i=t[r];if(a>=0&&i>=0&&a!==i)throw new Error("Incompatible shape during merge: ".concat(e," vs. ").concat(t));n[r]=a>=0?a:i}return n}var xl=function(){function e(t,n,r,a,o,s,c){Object(Yr.a)(this,e),this.name=t,this.dtype=n,this.maxSize=r,this.elementShape=a,this.identicalElementShapes=o,this.dynamicSize=s,this.clearAfterRead=c,this.tensors=[],this.closed_=!1,this.idTensor=Object(i.Pe)(0),Object(i.he)(this.idTensor)}return Object($r.a)(e,[{key:"id",get:function(){return this.idTensor.id}},{key:"closed",get:function(){return this.closed_}},{key:"clearAndClose",value:function(e){this.tensors.forEach((function(t){null!=e&&e.has(t.tensor.id)||t.tensor.dispose()})),this.tensors=[],this.closed_=!0,this.idTensor.dispose()}},{key:"size",value:function(){return this.tensors.length}},{key:"read",value:function(e){if(this.closed_)throw new Error("TensorArray ".concat(this.name," has already been closed."));if(e<0||e>=this.size())throw new Error("Tried to read from index ".concat(e,", but array size is: ").concat(this.size()));var t=this.tensors[e];if(t.cleared)throw new Error("TensorArray ".concat(this.name,": Could not read index ").concat(e," twice because it was cleared after a previous read ")+"(perhaps try setting clear_after_read = false?).");return this.clearAfterRead&&(t.cleared=!0),t.read=!0,t.tensor}},{key:"readMany",value:function(e){var t=this;return e.map((function(e){return t.read(e)}))}},{key:"write",value:function(e,t){if(this.closed_)throw new Error("TensorArray ".concat(this.name," has already been closed."));if(e<0||!this.dynamicSize&&e>=this.maxSize)throw new Error("Tried to write to index ".concat(e,", but array is not resizeable and size is: ").concat(this.maxSize));var n=this.tensors[e]||{};if(t.dtype!==this.dtype)throw new Error("TensorArray ".concat(this.name,": Could not write to TensorArray index ").concat(e,",\n          because the value dtype is ").concat(t.dtype,", but TensorArray dtype is ").concat(this.dtype,"."));if(0!==this.size()||null!=this.elementShape&&0!==this.elementShape.length||(this.elementShape=t.shape),vl(this.elementShape,t.shape,"TensorArray ".concat(this.name,": Could not write to TensorArray index ").concat(e,".")),n.read)throw new Error("TensorArray ".concat(this.name,": Could not write to TensorArray index ").concat(e,", because it has already been read."));if(n.written)throw new Error("TensorArray ".concat(this.name,": Could not write to TensorArray index ").concat(e,", because it has already been written."));n.tensor=t,Object(i.he)(t),n.written=!0,this.tensors[e]=n}},{key:"writeMany",value:function(e,t){var n=this;if(e.length!==t.length)throw new Error("TensorArray ".concat(this.name,": could not write multiple tensors,")+"because the index size: ".concat(e.length," is not the same as tensors size: ").concat(t.length,"."));e.forEach((function(e,r){return n.write(e,t[r])}))}},{key:"gather",value:function(e,t){if(t&&t!==this.dtype)throw new Error("TensorArray dtype is ".concat(this.dtype," but gather requested dtype ").concat(t));if(e)e=e.slice(0,this.size());else{e=[];for(var n=0;n<this.size();n++)e.push(n)}if(0===e.length)return Object(i.lf)([],[0].concat(this.elementShape));var r=this.readMany(e);return vl(this.elementShape,r[0].shape,"TensorArray shape mismatch: "),Object(i.gf)(r,0)}},{key:"concat",value:function(e){if(e&&e!==this.dtype)throw new Error("TensorArray dtype is ".concat(this.dtype," but concat requested dtype ").concat(e));if(0===this.size())return Object(i.lf)([],[0].concat(this.elementShape));for(var t=[],n=0;n<this.size();n++)t.push(n);var r=this.readMany(t);return vl(this.elementShape,r[0].shape,"TensorArray shape mismatch: tensor array shape (".concat(this.elementShape,") vs first tensor shape (").concat(r[0].shape,")")),Object(i.Dd)(r,0)}},{key:"scatter",value:function(e,t){if(t.dtype!==this.dtype)throw new Error("TensorArray dtype is ".concat(this.dtype," but tensor has dtype ").concat(t.dtype));if(e.length!==t.shape[0])throw new Error("Expected len(indices) == tensor.shape[0], but saw: ".concat(e.length," vs. ").concat(t.shape[0]));var n=Math.max.apply(Math,Object(Vn.a)(e));if(!this.dynamicSize&&n>=this.maxSize)throw new Error("Max index must be < array size (".concat(n,"  vs. ").concat(this.maxSize,")"));this.writeMany(e,Object(i.uf)(t,0))}},{key:"split",value:function(e,t){var n=this;if(t.dtype!==this.dtype)throw new Error("TensorArray dtype is ".concat(this.dtype," but tensor has dtype ").concat(t.dtype));var r=0,a=e.map((function(e){return r+=e}));if(r!==t.shape[0])throw new Error("Expected sum of lengths to be equal to\n          tensor.shape[0], but sum of lengths is\n        ".concat(r,", and tensor's shape is: ").concat(t.shape));if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error("TensorArray's size is not equal to the size of lengths (".concat(this.maxSize," vs. ").concat(e.length,"), ")+"and the TensorArray is not marked as dynamically resizeable");var o=0===r?0:t.size/r,s=[];Object(i.pf)((function(){t=Object(i.Ne)(t,[1,r,o]);for(var c=0;c<e.length;++c){var u=[0,0===c?0:a[c-1],0],l=[1,e[c],o];s[c]=Object(i.Ne)(Object(i.Ve)(t,u,l),n.elementShape)}return s}));for(var c=[],u=0;u<e.length;u++)c[u]=u;this.writeMany(c,s)}}]),e}(),kl=function(){function e(t,n,r){var a=arguments.length>3&&void 0!==arguments[3]?arguments[3]:-1;Object(Yr.a)(this,e),this.tensors=t,this.elementShape=n,this.elementDtype=r,null!=t&&t.forEach((function(e){if(r!==e.dtype)throw new Error("Invalid data types; op elements ".concat(r,", but list elements ").concat(e.dtype));vl(n,e.shape,"TensorList shape mismatch: "),Object(i.he)(e)})),this.idTensor=Object(i.Pe)(0),this.maxNumElements=a,Object(i.he)(this.idTensor)}return Object($r.a)(e,[{key:"id",get:function(){return this.idTensor.id}},{key:"copy",value:function(){return new e(Object(Vn.a)(this.tensors),this.elementShape,this.elementDtype)}},{key:"clearAndClose",value:function(e){this.tensors.forEach((function(t){null!=e&&e.has(t.id)||t.dispose()})),this.tensors.length=0,this.idTensor.dispose()}},{key:"size",value:function(){return this.tensors.length}},{key:"stack",value:function(e,t){var n=this,r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:-1;if(t!==this.elementDtype)throw new Error("Invalid data types; op elements ".concat(t,", but list elements ").concat(this.elementDtype));if(-1!==r&&this.tensors.length!==r)throw new Error("Operation expected a list with ".concat(r," elements but got a list with ").concat(this.tensors.length," elements."));vl(e,this.elementShape,"TensorList shape mismatch: ");var a=yl(this.elementShape,this.tensors,e);return Object(i.pf)((function(){var e=n.tensors.map((function(e){return Object(i.Ne)(e,a)}));return Object(i.gf)(e,0)}))}},{key:"popBack",value:function(e,t){if(t!==this.elementDtype)throw new Error("Invalid data types; op elements ".concat(t,", but list elements ").concat(this.elementDtype));if(0===this.size())throw new Error("Trying to pop from an empty list.");var n=yl(this.elementShape,this.tensors,e),r=this.tensors.pop();return vl(r.shape,e,"TensorList shape mismatch: "),Object(i.Ne)(r,n)}},{key:"pushBack",value:function(e){if(e.dtype!==this.elementDtype)throw new Error("Invalid data types; op elements ".concat(e.dtype,", but list elements ").concat(this.elementDtype));if(vl(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Object(i.he)(e),this.tensors.push(e)}},{key:"resize",value:function(e){if(e<0)throw new Error("TensorListResize expects size to be non-negative. Got: ".concat(e));if(-1!==this.maxNumElements&&e>this.maxNumElements)throw new Error("TensorListResize input size ".concat(e," is greater maxNumElement ").concat(this.maxNumElements,"."));this.tensors.length=e}},{key:"getItem",value:function(e,t,n){if(n!==this.elementDtype)throw new Error("Invalid data types; op elements ".concat(n,", but list elements ").concat(this.elementDtype));if(e<0||e>this.tensors.length)throw new Error("Trying to access element ".concat(e," in a list with ").concat(this.tensors.length," elements."));if(null==this.tensors[e])throw new Error("element at index ".concat(e," is null."));vl(this.tensors[e].shape,t,"TensorList shape mismatch: ");var r=yl(this.elementShape,this.tensors,t);return Object(i.Ne)(this.tensors[e],r)}},{key:"setItem",value:function(e,t){if(t.dtype!==this.elementDtype)throw new Error("Invalid data types; op elements ".concat(t.dtype,", but list elements ").concat(this.elementDtype));if(e<0||-1!==this.maxNumElements&&e>=this.maxNumElements)throw new Error("Trying to set element ".concat(e," in a list with max ").concat(this.maxNumElements," elements."));vl(this.elementShape,t.shape,"TensorList shape mismatch: "),Object(i.he)(t),this.tensors[e]=t}},{key:"gather",value:function(e,t,n){var r=this;if(t!==this.elementDtype)throw new Error("Invalid data types; op elements ".concat(t,", but list elements ").concat(this.elementDtype));vl(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());var a=yl(this.elementShape,this.tensors,n);return 0===e.length?Object(i.lf)([],[0].concat(a)):Object(i.pf)((function(){var t=e.map((function(e){return Object(i.Ne)(r.tensors[e],a)}));return Object(i.gf)(t,0)}))}},{key:"concat",value:function(e,t){var n=this;if(e&&e!==this.elementDtype)throw new Error("TensorList dtype is ".concat(this.elementDtype," but concat requested dtype ").concat(e));vl(this.elementShape,t,"TensorList shape mismatch: ");var r=yl(this.elementShape,this.tensors,t);return 0===this.size()?Object(i.lf)([],[0].concat(r)):Object(i.pf)((function(){var e=n.tensors.map((function(e){return Object(i.Ne)(e,r)}));return Object(i.Dd)(e,0)}))}}]),e}();function wl(e,t,n){var r=e.dtype;if(e.shape.length<1)throw new Error("Tensor must be at least a vector, but saw shape: ".concat(e.shape));if(e.dtype!==n)throw new Error("Invalid data types; op elements ".concat(e.dtype,", but list elements ").concat(n));vl(e.shape.slice(1),t,"TensorList shape mismatch: ");var a=Object(i.uf)(e);return new kl(a,t,r)}function jl(e,t,n){return new kl([],e,t,n)}function Sl(e,t,n,r){if(t.length!==e.shape[0])throw new Error("Expected len(indices) == tensor.shape[0], but saw: ".concat(t.length," vs. ").concat(e.shape[0]));var a=Math.max.apply(Math,Object(Vn.a)(t));if(null!=r&&-1!==r&&a>=r)throw new Error("Max index must be < array size (".concat(a,"  vs. ").concat(r,")"));var o=new kl([],n,e.dtype,r),s=Object(i.uf)(e,0);return t.forEach((function(e,t){o.setItem(e,s[t])})),o}function Nl(e,t,n){var r=0,a=t.map((function(e){return r+=e}));if(r!==e.shape[0])throw new Error("Expected sum of lengths to be equal to\n          tensor.shape[0], but sum of lengths is\n        ".concat(r,", and tensor's shape is: ").concat(e.shape));for(var o=Ol(e.shape.slice(1),n),s=0===r?0:e.size/r,c=Object(i.pf)((function(){var n=[];e=Object(i.Ne)(e,[1,r,s]);for(var c=0;c<t.length;++c){var u=[0,0===c?0:a[c-1],0],l=[1,t[c],s];n[c]=Object(i.Ne)(Object(i.Ve)(e,u,l),o)}return e.dispose(),n})),u=new kl([],n,e.dtype,t.length),l=0;l<c.length;l++)u.setItem(l,c[l]);return u}var Il=function(){var e=Object(go.a)(vo.a.mark((function e(t,n,r){var a,o,s,c,u,l,d,f,p,h,b,m,v,g,y,O,x,k,w,j,S,N,I,C,T,E,A,R,F,D,_,M,z,L,P,B,W,U,V,H,G,q,K,X,Y,$,Q,Z,J,ee,te,ne,re,ae,ie,oe,se,ce,ue,le,de,fe,pe,he,be,me,ve,ge,ye,Oe,xe,ke,we,je,Se,Ne,Ie,Ce,Te,Ee,Ae,Re,Fe,De,_e,Me,ze,Le,Pe,Be,We,Ue,Ve,He,Ge,qe;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:e.t0=t.op,e.next="If"===e.t0||"StatelessIf"===e.t0?3:"While"===e.t0||"StatelessWhile"===e.t0?15:"LoopCond"===e.t0?19:"Switch"===e.t0?21:"Merge"===e.t0?32:"Enter"===e.t0?37:"Exit"===e.t0?41:"NextIteration"===e.t0?44:"TensorArrayV3"===e.t0?47:"TensorArrayWriteV3"===e.t0?57:"TensorArrayReadV3"===e.t0?63:"TensorArrayGatherV3"===e.t0?67:"TensorArrayScatterV3"===e.t0?72:"TensorArrayConcatV3"===e.t0?78:"TensorArraySplitV3"===e.t0?82:"TensorArraySizeV3"===e.t0?88:"TensorArrayCloseV3"===e.t0?91:"TensorListSetItem"===e.t0?95:"TensorListGetItem"===e.t0?101:"TensorListScatterV2"===e.t0||"TensorListScatter"===e.t0?107:"TensorListReserve"===e.t0||"EmptyTensorList"===e.t0?114:"TensorListGather"===e.t0?121:"TensorListStack"===e.t0?127:"TensorListFromTensor"===e.t0?133:"TensorListConcat"===e.t0?139:"TensorListPushBack"===e.t0?144:"TensorListPopBack"===e.t0?149:"TensorListSplit"===e.t0?154:160;break;case 3:return a=Object(ll.d)("thenBranch",t,n,r),o=Object(ll.d)("elseBranch",t,n,r),s=Object(ll.d)("cond",t,n,r),c=Object(ll.d)("args",t,n,r),e.next=9,s.data();case 9:if(!e.sent[0]){e.next=14;break}return e.abrupt("return",r.functionMap[a].executeFunctionAsync(c,r.tensorArrayMap,r.tensorListMap));case 14:return e.abrupt("return",r.functionMap[o].executeFunctionAsync(c,r.tensorArrayMap,r.tensorListMap));case 15:return e.delegateYield(vo.a.mark((function e(){var a,i,o,s,c,u,l,d;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return a=Object(ll.d)("body",t,n,r),i=Object(ll.d)("cond",t,n,r),o=Object(ll.d)("args",t,n,r),e.next=5,r.functionMap[i].executeFunctionAsync(o,r.tensorArrayMap,r.tensorListMap);case 5:return s=e.sent,c=o.map((function(e){return e.id})),e.next=9,s[0].data();case 9:u=e.sent,s.forEach((function(e){e.kept||-1!==c.indexOf(e.id)||e.dispose()})),l=o,d=vo.a.mark((function e(){var t,n,o;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return t=l,e.next=3,r.functionMap[a].executeFunctionAsync(l,r.tensorArrayMap,r.tensorListMap);case 3:return l=e.sent,n=l.map((function(e){return e.id})),t.forEach((function(e){e.kept||-1!==c.indexOf(e.id)||-1!==n.indexOf(e.id)||e.dispose()})),e.next=8,r.functionMap[i].executeFunctionAsync(l,r.tensorArrayMap,r.tensorListMap);case 8:return o=e.sent,e.next=11,o[0].data();case 11:u=e.sent,o.forEach((function(e){e.kept||-1!==c.indexOf(e.id)||-1!==n.indexOf(e.id)||e.dispose()}));case 13:case"end":return e.stop()}}),e)}));case 13:if(!u[0]){e.next=17;break}return e.delegateYield(d(),"t0",15);case 15:e.next=13;break;case 17:return e.abrupt("return",{v:l});case 18:case"end":return e.stop()}}),e)}))(),"t1",16);case 16:if("object"!==typeof(u=e.t1)){e.next=19;break}return e.abrupt("return",u.v);case 19:return l=Object(ll.d)("pred",t,n,r),e.abrupt("return",[Object(ll.a)(l)]);case 21:return d=Object(ll.d)("pred",t,n,r),(f=Object(ll.d)("data",t,n,r)).kept||(f=Object(ll.a)(f)),e.next=26,d.data();case 26:if(!e.sent[0]){e.next=30;break}e.t2=[void 0,f],e.next=31;break;case 30:e.t2=[f,void 0];case 31:return e.abrupt("return",e.t2);case 32:if(!(p=t.inputNames.find((function(e){return void 0!==Object(ll.e)(e,n,r)})))){e.next=36;break}return h=Object(ll.e)(p,n,r),e.abrupt("return",[Object(ll.a)(h)]);case 36:return e.abrupt("return",void 0);case 37:return b=Object(ll.d)("frameName",t,n,r),m=Object(ll.d)("tensor",t,n,r),r.enterFrame(b),e.abrupt("return",[Object(ll.a)(m)]);case 41:return v=Object(ll.d)("tensor",t,n,r),r.exitFrame(),e.abrupt("return",[Object(ll.a)(v)]);case 44:return g=Object(ll.d)("tensor",t,n,r),r.nextIteration(),e.abrupt("return",[Object(ll.a)(g)]);case 47:return y=Object(ll.d)("size",t,n,r),O=Object(ll.d)("dtype",t,n,r),x=Object(ll.d)("elementShape",t,n,r),k=Object(ll.d)("dynamicSize",t,n,r),w=Object(ll.d)("clearAfterRead",t,n,r),j=Object(ll.d)("identicalElementShapes",t,n,r),S=Object(ll.d)("name",t,n,r),N=new xl(S,O,y,x,j,k,w),r.addTensorArray(N),e.abrupt("return",[N.idTensor,Object(i.Pe)(1)]);case 57:return I=Object(ll.d)("tensorArrayId",t,n,r),C=Object(ll.d)("index",t,n,r),T=Object(ll.d)("tensor",t,n,r),(E=r.getTensorArray(I.id)).write(C,T),e.abrupt("return",[E.idTensor]);case 63:return A=Object(ll.d)("tensorArrayId",t,n,r),R=Object(ll.d)("index",t,n,r),F=r.getTensorArray(A.id),e.abrupt("return",[F.read(R)]);case 67:return D=Object(ll.d)("tensorArrayId",t,n,r),_=Object(ll.d)("indices",t,n,r),M=Object(ll.d)("dtype",t,n,r),z=r.getTensorArray(D.id),e.abrupt("return",[z.gather(_,M)]);case 72:return L=Object(ll.d)("tensorArrayId",t,n,r),P=Object(ll.d)("indices",t,n,r),B=Object(ll.d)("tensor",t,n,r),(W=r.getTensorArray(L.id)).scatter(P,B),e.abrupt("return",[W.idTensor]);case 78:return U=Object(ll.d)("tensorArrayId",t,n,r),V=r.getTensorArray(U.id),H=Object(ll.d)("dtype",t,n,r),e.abrupt("return",[V.concat(H)]);case 82:return G=Object(ll.d)("tensorArrayId",t,n,r),q=Object(ll.d)("tensor",t,n,r),K=Object(ll.d)("lengths",t,n,r),(X=r.getTensorArray(G.id)).split(K,q),e.abrupt("return",[X.idTensor]);case 88:return Y=Object(ll.d)("tensorArrayId",t,n,r),$=r.getTensorArray(Y.id),e.abrupt("return",[Object(i.Pe)($.size(),"int32")]);case 91:return Q=Object(ll.d)("tensorArrayId",t,n,r),(Z=r.getTensorArray(Q.id)).clearAndClose(),e.abrupt("return",[Z.idTensor]);case 95:return J=Object(ll.d)("tensorListId",t,n,r),ee=Object(ll.d)("index",t,n,r),te=Object(ll.d)("tensor",t,n,r),(ne=r.getTensorList(J.id)).setItem(ee,te),e.abrupt("return",[ne.idTensor]);case 101:return re=Object(ll.d)("tensorListId",t,n,r),ae=Object(ll.d)("index",t,n,r),ie=Object(ll.d)("elementShape",t,n,r),oe=Object(ll.d)("elementDType",t,n,r),se=r.getTensorList(re.id),e.abrupt("return",[se.getItem(ae,ie,oe)]);case 107:return ce=Object(ll.d)("indices",t,n,r),ue=Object(ll.d)("tensor",t,n,r),le=Object(ll.d)("elementShape",t,n,r),de=Object(ll.d)("numElements",t,n,r),fe=Sl(ue,ce,le,de),r.addTensorList(fe),e.abrupt("return",[fe.idTensor]);case 114:return pe=Object(ll.d)("elementShape",t,n,r),he=Object(ll.d)("elementDType",t,n,r),be="TensorListReserve"===t.op?"numElements":"maxNumElements",me=Object(ll.d)(be,t,n,r),ve=jl(pe,he,me),r.addTensorList(ve),e.abrupt("return",[ve.idTensor]);case 121:return ge=Object(ll.d)("tensorListId",t,n,r),ye=Object(ll.d)("indices",t,n,r),Oe=Object(ll.d)("elementShape",t,n,r),xe=Object(ll.d)("elementDType",t,n,r),ke=r.getTensorList(ge.id),e.abrupt("return",[ke.gather(ye,xe,Oe)]);case 127:return we=Object(ll.d)("tensorListId",t,n,r),je=Object(ll.d)("elementShape",t,n,r),Se=Object(ll.d)("elementDType",t,n,r),Ne=Object(ll.d)("numElements",t,n,r),Ie=r.getTensorList(we.id),e.abrupt("return",[Ie.stack(je,Se,Ne)]);case 133:return Ce=Object(ll.d)("tensor",t,n,r),Te=Object(ll.d)("elementShape",t,n,r),Ee=Object(ll.d)("elementDType",t,n,r),Ae=wl(Ce,Te,Ee),r.addTensorList(Ae),e.abrupt("return",[Ae.idTensor]);case 139:return Re=Object(ll.d)("tensorListId",t,n,r),Fe=r.getTensorList(Re.id),De=Object(ll.d)("dtype",t,n,r),_e=Object(ll.d)("elementShape",t,n,r),e.abrupt("return",[Fe.concat(De,_e)]);case 144:return Me=Object(ll.d)("tensorListId",t,n,r),ze=Object(ll.d)("tensor",t,n,r),(Le=r.getTensorList(Me.id)).pushBack(ze),e.abrupt("return",[Le.idTensor]);case 149:return Pe=Object(ll.d)("tensorListId",t,n,r),Be=Object(ll.d)("elementShape",t,n,r),We=Object(ll.d)("elementDType",t,n,r),Ue=r.getTensorList(Pe.id),e.abrupt("return",[Ue.popBack(Be,We)]);case 154:return Ve=Object(ll.d)("tensor",t,n,r),He=Object(ll.d)("elementShape",t,n,r),Ge=Object(ll.d)("lengths",t,n,r),qe=Nl(Ve,Ge,He),r.addTensorList(qe),e.abrupt("return",[qe.idTensor]);case 160:throw TypeError("Node type ".concat(t.op," is not implemented"));case 161:case"end":return e.stop()}}),e)})));return function(t,n,r){return e.apply(this,arguments)}}(),Cl=n(37),Tl=n(259),El=n(271),Al=n(256),Rl=n(270);function Fl(e,t,n){var r=Object(ll.d)("fusedOps",e,t,n),a=Object(o.a)(r,2),i=a[0],s=a[1],c="biasadd"===i,u=!c,l="prelu"===s,d="fusedbatchnorm"===i,f=Object(ll.d)("numArgs",e,t,n);if(c){if(l&&2!==f)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!l&&c&&1!==f)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.")}if(d)throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported");var p=Object(ll.d)("strides",e,t,n),h=Object(ll.c)(e,t,n),b=Object(ll.d)("dataFormat",e,t,n).toUpperCase(),m=Object(ll.d)("dilations",e,t,n),v=Object(ll.d)("args",e,t,n),g=Object(o.a)(v,2),y=g[0],O=g[1];return u&&(O=y,y=void 0),{stride:p,pad:h,dataFormat:b,dilations:m,biasArg:y,preluArg:O,activationFunc:s,leakyreluAlpha:Object(ll.d)("leakyreluAlpha",e,t,n)}}var Dl=n(118),_l=n(267),Ml=n(272),zl=n(212),Ll=n(127),Pl=n(280),Bl=n(223),Wl=n(275);function Ul(e,t,n){return{boxes:Object(ll.d)("boxes",e,t,n),scores:Object(ll.d)("scores",e,t,n),maxOutputSize:Object(ll.d)("maxOutputSize",e,t,n),iouThreshold:Object(ll.d)("iouThreshold",e,t,n),scoreThreshold:Object(ll.d)("scoreThreshold",e,t,n),softNmsSigma:Object(ll.d)("softNmsSigma",e,t,n)}}var Vl=function(){var e=Object(go.a)(vo.a.mark((function e(t,n,r){var a,i,o,s,u,l,d,f,p,h,b,m,v,g,y,O,x,k,w,j,S,N,I,C;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:e.t0=t.op,e.next="NonMaxSuppressionV5"===e.t0?3:"NonMaxSuppressionV4"===e.t0?8:"NonMaxSuppressionV3"===e.t0||"NonMaxSuppressionV2"===e.t0?14:"Where"===e.t0?19:"ListDiff"===e.t0?26:27;break;case 3:return a=Ul(t,n,r),i=a.boxes,o=a.scores,s=a.maxOutputSize,u=a.iouThreshold,l=a.scoreThreshold,d=a.softNmsSigma,e.next=6,Cl.xb.nonMaxSuppressionWithScoreAsync(i,o,s,u,l,d);case 6:return f=e.sent,e.abrupt("return",[f.selectedIndices,f.selectedScores]);case 8:return p=Ul(t,n,r),h=p.boxes,b=p.scores,m=p.maxOutputSize,v=p.iouThreshold,g=p.scoreThreshold,y=Object(ll.d)("padToMaxOutputSize",t,n,r),e.next=12,Cl.xb.nonMaxSuppressionPaddedAsync(h,b,m,v,g,y);case 12:return O=e.sent,e.abrupt("return",[O.selectedIndices,O.validOutputs]);case 14:return x=Ul(t,n,r),k=x.boxes,w=x.scores,j=x.maxOutputSize,S=x.iouThreshold,N=x.scoreThreshold,e.next=17,Cl.xb.nonMaxSuppressionAsync(k,w,j,S,N);case 17:return e.t1=e.sent,e.abrupt("return",[e.t1]);case 19:return I=c.a(Object(ll.d)("condition",t,n,r),"bool"),e.next=22,Bl.a(I);case 22:return e.t2=e.sent,C=[e.t2],I.dispose(),e.abrupt("return",C);case 26:return e.abrupt("return",Wl.a(Object(ll.d)("x",t,n,r),Object(ll.d)("y",t,n,r)));case 27:throw TypeError("Node type ".concat(t.op," is not implemented"));case 28:case"end":return e.stop()}}),e)})));return function(t,n,r){return e.apply(this,arguments)}}(),Hl=n(70),Gl=function(){function e(t,n){Object(Yr.a)(this,e),this.keyDType=t,this.valueDType=n,this.handle=Object(i.Pe)(0),this.tensorMap=new Map,Object(i.he)(this.handle)}return Object($r.a)(e,[{key:"id",get:function(){return this.handle.id}},{key:"clearAndClose",value:function(){this.tensorMap.forEach((function(e){return e.dispose()})),this.tensorMap.clear(),this.handle.dispose()}},{key:"size",value:function(){return this.tensorMap.size}},{key:"tensorSize",value:function(){return h.a(this.size(),"int32")}},{key:"import",value:function(){var e=Object(go.a)(vo.a.mark((function e(t,n){var r,a=this;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return this.checkKeyAndValueTensor(t,n),e.next=3,t.data();case 3:return r=e.sent,this.tensorMap.forEach((function(e){return e.dispose()})),this.tensorMap.clear(),e.abrupt("return",Object(i.pf)((function(){var e=Object(i.uf)(n),t=r.length,o=e.length;i.wf.assert(t===o,(function(){return"The number of elements doesn't match, keys has "+"".concat(t," elements, the values has ").concat(o," ")+"elements."}));for(var s=0;s<t;s++){var c=r[s],u=e[s];Object(i.he)(u),a.tensorMap.set(c,u)}return a.handle})));case 7:case"end":return e.stop()}}),e,this)})));return function(t,n){return e.apply(this,arguments)}}()},{key:"find",value:function(){var e=Object(go.a)(vo.a.mark((function e(t,n){var r,a=this;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return this.checkKeyAndValueTensor(t,n),e.next=3,t.data();case 3:return r=e.sent,e.abrupt("return",Object(i.pf)((function(){for(var e=[],t=0;t<r.length;t++){var o=r[t],s=a.findWithDefault(o,n);e.push(s)}return Object(i.gf)(e)})));case 5:case"end":return e.stop()}}),e,this)})));return function(t,n){return e.apply(this,arguments)}}()},{key:"findWithDefault",value:function(e,t){var n=this.tensorMap.get(e);return null!=n?n:t}},{key:"checkKeyAndValueTensor",value:function(e,t){if(e.dtype!==this.keyDType)throw new Error("Expect key dtype ".concat(this.keyDType,", but got ")+"".concat(e.dtype));if(t.dtype!==this.valueDType)throw new Error("Expect value dtype ".concat(this.valueDType,", but got ")+"".concat(t.dtype))}}]),e}(),ql=function(){var e=Object(go.a)(vo.a.mark((function e(t,n,r,a){var i,o,s,c,u,l,d,f,p,h,b,m,v;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:e.t0=t.op,e.next="HashTable"===e.t0||"HashTableV2"===e.t0?3:"LookupTableImport"===e.t0||"LookupTableImportV2"===e.t0?8:"LookupTableFind"===e.t0||"LookupTableFindV2"===e.t0?16:"LookupTableSize"===e.t0||"LookupTableSizeV2"===e.t0?24:27;break;case 3:return i=Object(ll.d)("keyDType",t,n,r),o=Object(ll.d)("valueDType",t,n,r),s=new Gl(i,o),a.addHashTable(t.name,s),e.abrupt("return",[s.handle]);case 8:return c=Object(ll.d)("tableHandle",t,n,r,a),u=Object(ll.d)("keys",t,n,r),l=Object(ll.d)("values",t,n,r),d=a.getHashTableById(c.id),e.next=14,d.import(u,l);case 14:return e.t1=e.sent,e.abrupt("return",[e.t1]);case 16:return f=Object(ll.d)("tableHandle",t,n,r,a),p=Object(ll.d)("keys",t,n,r),h=Object(ll.d)("defaultValue",t,n,r),b=a.getHashTableById(f.id),e.next=22,b.find(p,h);case 22:return e.t2=e.sent,e.abrupt("return",[e.t2]);case 24:return m=Object(ll.d)("tableHandle",t,n,r,a),v=a.getHashTableById(m.id),e.abrupt("return",[v.tensorSize()]);case 27:throw TypeError("Node type ".concat(t.op," is not implemented"));case 28:case"end":return e.stop()}}),e)})));return function(t,n,r,a){return e.apply(this,arguments)}}(),Kl=n(261),Xl=n(284),Yl=n(195),$l=n(260),Ql=n(281),Zl=n(282);function Jl(e,t,n,a){var s=function(e,t,n){switch(e.category){case"arithmetic":return i.pf((function(){return function(e,t,n){switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[T.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"AddN":return[pl.a(Object(ll.d)("tensors",e,t,n))];case"FloorMod":case"Mod":return[xr.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"Mul":return[u.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"RealDiv":case"Div":return[f.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"DivNoNan":return[Yn.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"FloorDiv":return[tr.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"Sub":return[v.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"Minimum":return[yr.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"Maximum":return[gn.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"Pow":return[wt.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"SquaredDifference":return[Wr.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"basic_math":return i.pf((function(){return function(e,t,n){switch(e.op){case"Abs":case"ComplexAbs":return[Sn.a(Object(ll.d)("x",e,t,n))];case"Acos":return[In.a(Object(ll.d)("x",e,t,n))];case"Acosh":return[Cn.a(Object(ll.d)("x",e,t,n))];case"Asin":return[Fn.a(Object(ll.d)("x",e,t,n))];case"Asinh":return[Dn.a(Object(ll.d)("x",e,t,n))];case"Atan":return[_n.a(Object(ll.d)("x",e,t,n))];case"Atan2":return[Mn.a(Object(ll.d)("x",e,t,n),Object(ll.d)("y",e,t,n))];case"Atanh":return[zn.a(Object(ll.d)("x",e,t,n))];case"Ceil":return[Wn.a(Object(ll.d)("x",e,t,n))];case"Complex":return[hl.a(Object(ll.d)("real",e,t,n),Object(ll.d)("imag",e,t,n))];case"Cos":return[Vt.a(Object(ll.d)("x",e,t,n))];case"Cosh":return[Gt.a(Object(ll.d)("x",e,t,n))];case"Elu":return[Qn.a(Object(ll.d)("x",e,t,n))];case"Erf":return[Zn.a(Object(ll.d)("x",e,t,n))];case"Exp":return[Se.a(Object(ll.d)("x",e,t,n))];case"Expm1":return[Jn.a(Object(ll.d)("x",e,t,n))];case"Floor":return[ft.a(Object(ll.d)("x",e,t,n))];case"Log":return[kt.a(Object(ll.d)("x",e,t,n))];case"Log1p":return[fr.a(Object(ll.d)("x",e,t,n))];case"Imag":return[bl.a(Object(ll.d)("x",e,t,n))];case"Neg":return[p.a(Object(ll.d)("x",e,t,n))];case"Reciprocal":return[Tr.a(Object(ll.d)("x",e,t,n))];case"Real":return[ml.a(Object(ll.d)("x",e,t,n))];case"Relu":return[Er.a(Object(ll.d)("x",e,t,n))];case"Round":return[_r.a(Object(ll.d)("x",e,t,n))];case"Selu":return[Mr.a(Object(ll.d)("x",e,t,n))];case"Sigmoid":return[Qt.a(Object(ll.d)("x",e,t,n))];case"Sin":return[fe.a(Object(ll.d)("x",e,t,n))];case"Sign":return[Lr.a(Object(ll.d)("x",e,t,n))];case"Sinh":return[he.a(Object(ll.d)("x",e,t,n))];case"Softplus":return[Br.a(Object(ll.d)("x",e,t,n))];case"Sqrt":return[b.a(Object(ll.d)("x",e,t,n))];case"Square":return[m.a(Object(ll.d)("x",e,t,n))];case"Tanh":return[Gr.a(Object(ll.d)("x",e,t,n))];case"Tan":return[Hr.a(Object(ll.d)("x",e,t,n))];case"ClipByValue":return[Un.a(Object(ll.d)("x",e,t,n),Object(ll.d)("clipValueMin",e,t,n),Object(ll.d)("clipValueMax",e,t,n))];case"Relu6":return[Ar.a(Object(ll.d)("x",e,t,n))];case"Rsqrt":return[Re.a(Object(ll.e)(e.inputNames[0],t,n))];case"Prod":return[Cr.a(Object(ll.d)("x",e,t,n),Object(ll.d)("axes",e,t,n))];case"LeakyRelu":return[sr.a(Object(ll.d)("x",e,t,n),Object(ll.d)("alpha",e,t,n))];case"Prelu":return[Ir.a(Object(ll.d)("x",e,t,n),Object(ll.d)("alpha",e,t,n))];case"IsNan":return[or.a(Object(ll.e)(e.inputNames[0],t,n))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"control":return Il(e,t,n);case"convolution":return i.pf((function(){return function(e,t,n){switch(e.op){case"Conv1D":var r=Object(ll.d)("stride",e,t,n),a=Object(ll.d)("pad",e,t,n),i=Object(ll.d)("dataFormat",e,t,n).toUpperCase(),o=Object(ll.d)("dilation",e,t,n);return[Hn.a(Object(ll.d)("x",e,t,n),Object(ll.d)("filter",e,t,n),r,a,i,o)];case"Conv2D":var s=Object(ll.d)("strides",e,t,n),c=Object(ll.c)(e,t,n),u=Object(ll.d)("dataFormat",e,t,n).toUpperCase(),l=Object(ll.d)("dilations",e,t,n);return[se.a(Object(ll.d)("x",e,t,n),Object(ll.d)("filter",e,t,n),[s[1],s[2]],c,u,[l[1],l[2]])];case"_FusedConv2D":var d=Fl(e,t,n),f=d.stride,p=d.pad,h=d.dataFormat,b=d.dilations,m=d.biasArg,v=d.preluArg,g=d.activationFunc,y=d.leakyreluAlpha;return[Cl.qb.conv2d({x:Object(ll.d)("x",e,t,n),filter:Object(ll.d)("filter",e,t,n),strides:[f[1],f[2]],pad:p,dataFormat:h,dilations:[b[1],b[2]],bias:m,activation:g,preluActivationWeights:v,leakyreluAlpha:y})];case"FusedDepthwiseConv2dNative":var O=Fl(e,t,n),x=O.stride,k=O.pad,w=O.dataFormat,j=O.dilations,S=O.biasArg,N=O.preluArg,I=O.activationFunc,C=O.leakyreluAlpha;return[Cl.qb.depthwiseConv2d({x:Object(ll.d)("x",e,t,n),filter:Object(ll.d)("filter",e,t,n),strides:[x[1],x[2]],pad:k,dataFormat:w,dilations:[j[1],j[2]],bias:S,activation:I,preluActivationWeights:N,leakyreluAlpha:C})];case"Conv2DBackpropInput":case"Conv2dTranspose":var T=Object(ll.d)("outputShape",e,t,n),E=Object(ll.d)("strides",e,t,n),A=Object(ll.c)(e,t,n);return[Gn.a(Object(ll.d)("x",e,t,n),Object(ll.d)("filter",e,t,n),T,[E[1],E[2]],A)];case"DepthwiseConv2dNative":case"DepthwiseConv2d":var R=Object(ll.d)("strides",e,t,n),F=Object(ll.c)(e,t,n),D=Object(ll.d)("dilations",e,t,n),_=Object(ll.d)("dataFormat",e,t,n).toUpperCase();return[Kn.a(Object(ll.d)("input",e,t,n),Object(ll.d)("filter",e,t,n),[R[1],R[2]],F,_,[D[1],D[2]])];case"Conv3D":var M=Object(ll.d)("strides",e,t,n),z=Object(ll.d)("pad",e,t,n),L=Object(ll.d)("dataFormat",e,t,n).toUpperCase(),P=Object(ll.d)("dilations",e,t,n);return[Tl.a(Object(ll.d)("x",e,t,n),Object(ll.d)("filter",e,t,n),[M[1],M[2],M[3]],z,L,[P[1],P[2],P[3]])];case"AvgPool":var B=Object(ll.d)("strides",e,t,n),W=Object(ll.d)("pad",e,t,n),U=Object(ll.d)("kernelSize",e,t,n);return[Ln.a(Object(ll.d)("x",e,t,n),[U[1],U[2]],[B[1],B[2]],W)];case"MaxPool":var V=Object(ll.d)("strides",e,t,n),H=Object(ll.d)("pad",e,t,n),G=Object(ll.d)("kernelSize",e,t,n);return[br.a(Object(ll.d)("x",e,t,n),[G[1],G[2]],[V[1],V[2]],H)];case"MaxPoolWithArgmax":var q=Object(ll.d)("strides",e,t,n),K=Object(ll.d)("pad",e,t,n),X=Object(ll.d)("kernelSize",e,t,n),Y=Object(ll.d)("includeBatchInIndex",e,t,n),$=El.a(Object(ll.d)("x",e,t,n),[X[1],X[2]],[q[1],q[2]],K,Y);return[$.result,$.indexes];case"AvgPool3D":var Q=Object(ll.d)("strides",e,t,n),Z=Object(ll.d)("pad",e,t,n),J=Object(ll.d)("kernelSize",e,t,n);return[Al.a(Object(ll.d)("x",e,t,n),[J[1],J[2],J[3]],[Q[1],Q[2],Q[3]],Z)];case"MaxPool3D":var ee=Object(ll.d)("strides",e,t,n),te=Object(ll.d)("pad",e,t,n),ne=Object(ll.d)("kernelSize",e,t,n);return[Rl.a(Object(ll.d)("x",e,t,n),[ne[1],ne[2],ne[3]],[ee[1],ee[2],ee[3]],te)];case"Dilation2D":var re=Object(ll.d)("strides",e,t,n),ae=Object(ll.d)("pad",e,t,n),ie=Object(ll.d)("dilations",e,t,n),oe=re[1],ce=re[2],ue=ie[1],le=ie[2];return[Xn.a(Object(ll.d)("x",e,t,n),Object(ll.d)("filter",e,t,n),[oe,ce],ae,[ue,le],"NHWC")];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"creation":return i.pf((function(){return function(e,t,n){switch(e.op){case"Fill":var r=Object(ll.d)("shape",e,t,n),a=Object(ll.d)("dtype",e,t,n),i=Object(ll.d)("value",e,t,n);return[Dl.a(r,i,a)];case"LinSpace":var o=Object(ll.d)("start",e,t,n),s=Object(ll.d)("stop",e,t,n),c=Object(ll.d)("num",e,t,n);return[_l.a(o,s,c)];case"Multinomial":var u=Object(ll.d)("logits",e,t,n),l=Object(ll.d)("numSamples",e,t,n),d=Object(ll.d)("seed",e,t,n);return[Ml.a(u,l,d)];case"OneHot":var f=Object(ll.d)("indices",e,t,n),p=Object(ll.d)("depth",e,t,n),h=Object(ll.d)("onValue",e,t,n),b=Object(ll.d)("offValue",e,t,n);return[jr.a(f,p,h,b)];case"Ones":return[ot.a(Object(ll.d)("shape",e,t,n),Object(ll.d)("dtype",e,t,n))];case"OnesLike":return[Sr.a(Object(ll.d)("x",e,t,n))];case"RandomUniform":return[zl.a(Object(ll.d)("shape",e,t,n),Object(ll.d)("minval",e,t,n),Object(ll.d)("maxval",e,t,n),Object(ll.d)("dtype",e,t,n))];case"Range":var m=Object(ll.d)("start",e,t,n),v=Object(ll.d)("stop",e,t,n),g=Object(ll.d)("step",e,t,n);return[Ll.a(m,v,g,Object(ll.d)("dtype",e,t,n))];case"TruncatedNormal":var y=Object(ll.d)("shape",e,t,n),O=Object(ll.d)("mean",e,t,n),x=Object(ll.d)("stdDev",e,t,n),k=Object(ll.d)("seed",e,t,n);return[Pl.a(y,O,x,Object(ll.d)("dtype",e,t,n),k)];case"Zeros":return[mt.a(Object(ll.d)("shape",e,t,n),Object(ll.d)("dtype",e,t,n))];case"ZerosLike":return[S.a(Object(ll.d)("x",e,t,n))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"dynamic":return Vl(e,t,n);case"evaluation":return i.pf((function(){return function(e,t,n){switch(e.op){case"TopKV2":var r=Object(ll.d)("x",e,t,n),a=Object(ll.d)("k",e,t,n),i=Object(ll.d)("sorted",e,t,n),o=qr.a(r,a,i);return[o.values,o.indices];case"Unique":var s=Object(ll.d)("x",e,t,n),c=Kr.a(s);return[c.values,c.indices];case"UniqueV2":var u=Object(ll.d)("x",e,t,n),l=Object(ll.d)("axis",e,t,n),d=Kr.a(u,l);return[d.values,d.indices];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"image":return i.pf((function(){return function(e,t,n){switch(e.op){case"ResizeBilinear":var r=Object(ll.d)("images",e,t,n),a=Object(ll.d)("size",e,t,n),i=Object(ll.d)("alignCorners",e,t,n),o=Object(ll.d)("halfPixelCenters",e,t,n);return[Cl.xb.resizeBilinear(r,[a[0],a[1]],i,o)];case"ResizeNearestNeighbor":var s=Object(ll.d)("images",e,t,n),c=Object(ll.d)("size",e,t,n),u=Object(ll.d)("alignCorners",e,t,n),l=Object(ll.d)("halfPixelCenters",e,t,n);return[Cl.xb.resizeNearestNeighbor(s,[c[0],c[1]],u,l)];case"CropAndResize":var d=Object(ll.d)("image",e,t,n),f=Object(ll.d)("boxes",e,t,n),p=Object(ll.d)("boxInd",e,t,n),h=Object(ll.d)("cropSize",e,t,n),b=Object(ll.d)("method",e,t,n),m=Object(ll.d)("extrapolationValue",e,t,n);return[Cl.xb.cropAndResize(d,f,p,h,b,m)];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"graph":return i.pf((function(){return function(e,t,n){switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":var r=Object(ll.d)("default",e,t,n);return[Object(ll.e)(e.name,t,n)||r];case"Placeholder":return[Object(ll.e)(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":var a=Object(ll.d)("x",e,t,n);return[Object(ll.a)(a)];case"IdentityN":return Object(ll.d)("x",e,t,n).map((function(e){return Object(ll.a)(e)}));case"Snapshot":var i=Object(ll.d)("x",e,t,n);return[Object(ll.a)(i)];case"Shape":return[Hl.a(Object(ll.d)("x",e,t,n).shape,"int32")];case"ShapeN":return Object(ll.d)("x",e,t,n).map((function(e){return Hl.a(e.shape)}));case"Size":return[h.a(Object(ll.d)("x",e,t,n).size,"int32")];case"Rank":return[h.a(Object(ll.d)("x",e,t,n).rank,"int32")];case"NoOp":return[h.a(1)];case"Print":var o=Object(ll.d)("x",e,t,n),s=Object(ll.d)("data",e,t,n),c=Object(ll.d)("message",e,t,n),u=Object(ll.d)("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(c);for(var l=0;l<s.length;l++)console.log(Array.prototype.slice.call(s[l].dataSync()).slice(0,u));return[o];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"logical":return i.pf((function(){return function(e,t,n){switch(e.op){case"Equal":return[Qe.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"NotEqual":return[wr.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"Greater":return[He.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"GreaterEqual":return[Y.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"Less":return[et.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"LessEqual":return[$.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"LogicalAnd":return[Q.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"LogicalNot":return[zt.a(Object(ll.d)("a",e,t,n))];case"LogicalOr":return[pr.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];case"Select":case"SelectV2":return[Z.a(Object(ll.d)("condition",e,t,n),Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"matrices":return i.pf((function(){return function(e,t,n){switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[U.a(Object(ll.d)("a",e,t,n),Object(ll.d)("b",e,t,n),Object(ll.d)("transposeA",e,t,n),Object(ll.d)("transposeB",e,t,n))];case"Einsum":return[Kl.a.apply(r,[Object(ll.d)("equation",e,t,n)].concat(Object(Vn.a)(Object(ll.d)("tensors",e,t,n))))];case"Transpose":return[ge.a(Object(ll.d)("x",e,t,n),Object(ll.d)("perm",e,t,n))];case"_FusedMatMul":var a=Object(ll.d)("fusedOps",e,t,n),i=Object(o.a)(a,2),s=i[0],c=i[1],u="biasadd"===s,l="prelu"===c,d=Object(ll.d)("numArgs",e,t,n),f=Object(ll.d)("leakyreluAlpha",e,t,n);if(u){if(l&&2!==d)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!l&&1!==d)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}var p=Object(ll.d)("args",e,t,n),h=Object(o.a)(p,2),b=h[0],m=h[1];return[Cl.qb.matMul({a:Object(ll.d)("a",e,t,n),b:Object(ll.d)("b",e,t,n),transposeA:Object(ll.d)("transposeA",e,t,n),transposeB:Object(ll.d)("transposeB",e,t,n),bias:b,activation:c,preluActivationWeights:m,leakyreluAlpha:f})];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"normalization":return i.pf((function(){return function(e,t,n){switch(e.op){case"FusedBatchNorm":case"FusedBatchNormV2":case"FusedBatchNormV3":return[Pn.a(Object(ll.d)("x",e,t,n),Object(ll.d)("mean",e,t,n),Object(ll.d)("variance",e,t,n),Object(ll.d)("offset",e,t,n),Object(ll.d)("scale",e,t,n),Object(ll.d)("epsilon",e,t,n))];case"LRN":return[cr.a(Object(ll.d)("x",e,t,n),Object(ll.d)("radius",e,t,n),Object(ll.d)("bias",e,t,n),Object(ll.d)("alpha",e,t,n),Object(ll.d)("beta",e,t,n))];case"Softmax":return[Pr.a(Object(ll.d)("x",e,t,n))];case"LogSoftmax":return[lr.a(Object(ll.d)("x",e,t,n))];case"SparseToDense":return[Xl.a(Object(ll.d)("sparseIndices",e,t,n),Object(ll.d)("outputShape",e,t,n),Object(ll.d)("sparseValues",e,t,n),Object(ll.d)("defaultValue",e,t,n))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"reduction":return i.pf((function(){return function(e,t,n){switch(e.op){case"Max":var r=Object(ll.d)("axis",e,t,n),a=Object(ll.d)("keepDims",e,t,n);return[mr.a(Object(ll.d)("x",e,t,n),r,a)];case"Mean":var i=Object(ll.d)("axis",e,t,n),o=Object(ll.d)("keepDims",e,t,n);return[vr.a(Object(ll.d)("x",e,t,n),i,o)];case"Min":var s=Object(ll.d)("axis",e,t,n),c=Object(ll.d)("keepDims",e,t,n);return[gr.a(Object(ll.d)("x",e,t,n),s,c)];case"Sum":var u=Object(ll.d)("axis",e,t,n),l=Object(ll.d)("keepDims",e,t,n);return[k.a(Object(ll.d)("x",e,t,n),u,l)];case"All":var d=Object(ll.d)("axis",e,t,n),f=Object(ll.d)("keepDims",e,t,n);return[Tn.a(Object(ll.d)("x",e,t,n),d,f)];case"Any":var p=Object(ll.d)("axis",e,t,n),h=Object(ll.d)("keepDims",e,t,n);return[En.a(Object(ll.d)("x",e,t,n),p,h)];case"ArgMax":var b=Object(ll.d)("axis",e,t,n);return[An.a(Object(ll.d)("x",e,t,n),b)];case"ArgMin":var m=Object(ll.d)("axis",e,t,n);return[Rn.a(Object(ll.d)("x",e,t,n),m)];case"Prod":var v=Object(ll.d)("axis",e,t,n),g=Object(ll.d)("keepDims",e,t,n);return[Cr.a(Object(ll.d)("x",e,t,n),v,g)];case"Cumsum":var y=Object(ll.d)("axis",e,t,n),O=Object(ll.d)("exclusive",e,t,n),x=Object(ll.d)("reverse",e,t,n);return[ve.a(Object(ll.d)("x",e,t,n),y,O,x)];case"Bincount":var w=Object(ll.d)("x",e,t,n),j=Object(ll.d)("weights",e,t,n),S=Object(ll.d)("size",e,t,n);return[Yl.a(w,j,S)];case"DenseBincount":var N=Object(ll.d)("x",e,t,n),I=Object(ll.d)("weights",e,t,n),C=Object(ll.d)("size",e,t,n),T=Object(ll.d)("binaryOutput",e,t,n);return[$l.a(N,I,C,T)];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"slice_join":return i.pf((function(){return function(e,t,n){switch(e.op){case"ConcatV2":case"Concat":var r=Object(ll.d)("n",e,t,n),a=Object(ll.d)("axis",e,t,n),o=Object(ll.d)("tensors",e,t,n);return o=o.slice(0,r),[tn.a(o,a)];case"Gather":var s=Object(ll.d)("x",e,t,n),u=Object(ll.d)("indices",e,t,n);return[vn.a(s,c.a(u,"int32"),0)];case"GatherV2":var l=Object(ll.d)("axis",e,t,n),d=Object(ll.d)("batchDims",e,t,n),f=Object(ll.d)("x",e,t,n),p=Object(ll.d)("indices",e,t,n);return[vn.a(f,c.a(p,"int32"),l,d)];case"Reverse":for(var h=Object(ll.d)("dims",e,t,n),b=[],m=0;m<h.length;m++)h[m]&&b.push(m);var v=Object(ll.d)("x",e,t,n);return[Ft.a(v,b)];case"ReverseV2":var g=Object(ll.d)("axis",e,t,n),y=Object(ll.d)("x",e,t,n);return[Ft.a(y,g)];case"Slice":var O=Object(ll.d)("begin",e,t,n),k=Object(ll.d)("size",e,t,n);return[lt.a(Object(ll.d)("x",e,t,n),O,k)];case"StridedSlice":var w=Object(ll.d)("begin",e,t,n),j=Object(ll.d)("end",e,t,n),S=Object(ll.d)("strides",e,t,n),N=Object(ll.d)("beginMask",e,t,n),I=Object(ll.d)("endMask",e,t,n),C=Object(ll.d)("ellipsisMask",e,t,n),T=Object(ll.d)("newAxisMask",e,t,n),E=Object(ll.d)("shrinkAxisMask",e,t,n),A=Object(ll.d)("x",e,t,n);return[Vr.a(A,w,j,S,N,I,C,T,E)];case"Pack":return Object(i.pf)((function(){var r=Object(ll.d)("axis",e,t,n),a=Object(ll.d)("tensors",e,t,n),o=a[0].shape,s=Ur.a(a[0]).shape,c=a.map((function(e){var t=i.wf.arraysEqual(e.shape,o);if(!t&&!i.wf.arraysEqual(Ur.a(e).shape,s))throw new Error("the input tensors shape does not match");return t?e:x.a(e,o)}));return[hn.a(c,r)]}));case"Unpack":var R=Object(ll.d)("axis",e,t,n),F=Object(ll.d)("tensor",e,t,n);return yt.a(F,R);case"Tile":var D=Object(ll.d)("reps",e,t,n);return[Fe.a(Object(ll.d)("x",e,t,n),D)];case"Split":case"SplitV":var _=Object(ll.d)("axis",e,t,n),M=Object(ll.d)("numOrSizeSplits",e,t,n),z=Object(ll.d)("x",e,t,n);return te.a(z,M,_);case"ScatterNd":var L=Object(ll.d)("indices",e,t,n),P=Object(ll.d)("values",e,t,n),B=Object(ll.d)("shape",e,t,n);return[Ql.a(L,P,B)];case"GatherNd":var W=Object(ll.d)("x",e,t,n),U=Object(ll.d)("indices",e,t,n);return[Zl.a(W,U)];case"SparseToDense":var V=Object(ll.d)("sparseIndices",e,t,n),H=Object(ll.d)("outputShape",e,t,n),G=Object(ll.d)("sparseValues",e,t,n),q=Object(ll.d)("defaultValue",e,t,n);return[Xl.a(V,G,H,G.dtype===q.dtype?q:c.a(q,G.dtype))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"sparse":return i.pf((function(){return function(e,t,n){switch(e.op){case"SparseFillEmptyRows":var r=Cl.md.sparseFillEmptyRows(Object(ll.d)("indices",e,t,n),Object(ll.d)("values",e,t,n),Object(ll.d)("denseShape",e,t,n),Object(ll.d)("defaultValue",e,t,n));return[r.outputIndices,r.outputValues,r.emptyRowIndicator,r.reverseIndexMap];case"SparseReshape":var a=Cl.md.sparseReshape(Object(ll.d)("inputIndices",e,t,n),Object(ll.d)("inputShape",e,t,n),Object(ll.d)("newShape",e,t,n));return[a.outputIndices,a.outputShape];case"SparseSegmentMean":return[Cl.md.sparseSegmentMean(Object(ll.d)("data",e,t,n),Object(ll.d)("indices",e,t,n),Object(ll.d)("segmentIds",e,t,n))];case"SparseSegmentSum":return[Cl.md.sparseSegmentSum(Object(ll.d)("data",e,t,n),Object(ll.d)("indices",e,t,n),Object(ll.d)("segmentIds",e,t,n))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"spectral":return i.pf((function(){return function(e,t,n){switch(e.op){case"FFT":return[er.a(Object(ll.d)("x",e,t,n))];case"IFFT":return[nr.a(Object(ll.d)("x",e,t,n))];case"RFFT":return[Dr.a(Object(ll.d)("x",e,t,n))];case"IRFFT":return[rr.a(Object(ll.d)("x",e,t,n))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"string":return i.pf((function(){return function(e,t,n){switch(e.op){case"StringNGrams":var r=Cl.xd.stringNGrams(Object(ll.d)("data",e,t,n),Object(ll.d)("dataSplits",e,t,n),Object(ll.d)("separator",e,t,n),Object(ll.d)("nGramWidths",e,t,n),Object(ll.d)("leftPad",e,t,n),Object(ll.d)("rightPad",e,t,n),Object(ll.d)("padWidth",e,t,n),Object(ll.d)("preserveShortSequences",e,t,n));return[r.nGrams,r.nGramsSplits];case"StringSplit":var a=Cl.xd.stringSplit(Object(ll.d)("input",e,t,n),Object(ll.d)("delimiter",e,t,n),Object(ll.d)("skipEmpty",e,t,n));return[a.indices,a.values,a.shape];case"StringToHashBucketFast":return[Cl.xd.stringToHashBucketFast(Object(ll.d)("input",e,t,n),Object(ll.d)("numBuckets",e,t,n))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"transformation":return i.pf((function(){return function(e,t,n){switch(e.op){case"Cast":return[c.a(Object(ll.d)("x",e,t,n),Object(ll.d)("dtype",e,t,n))];case"ExpandDims":var r=Object(ll.d)("axis",e,t,n);return[mn.a(Object(ll.d)("x",e,t,n),r)];case"Squeeze":var a=Object(ll.d)("axis",e,t,n);return[Ur.a(Object(ll.d)("x",e,t,n),a)];case"Reshape":return[x.a(Object(ll.d)("x",e,t,n),Object(ll.d)("shape",e,t,n))];case"MirrorPad":return[Or.a(Object(ll.d)("x",e,t,n),Object(ll.d)("padding",e,t,n),Object(ll.d)("mode",e,t,n))];case"PadV2":case"Pad":return[Kt.a(Object(ll.d)("x",e,t,n),Object(ll.d)("padding",e,t,n),Object(ll.d)("constantValue",e,t,n))];case"SpaceToBatchND":var i=Object(ll.d)("blockShape",e,t,n),o=Object(ll.d)("paddings",e,t,n);return[H.a(Object(ll.d)("x",e,t,n),i,o)];case"BatchToSpaceND":var s=Object(ll.d)("blockShape",e,t,n),u=Object(ll.d)("crops",e,t,n);return[Jt.a(Object(ll.d)("x",e,t,n),s,u)];case"DepthToSpace":var l=Object(ll.d)("blockSize",e,t,n),d=Object(ll.d)("dataFormat",e,t,n).toUpperCase();return[qn.a(Object(ll.d)("x",e,t,n),l,d)];case"BroadcastTo":return[Bn.a(Object(ll.d)("x",e,t,n),Object(ll.d)("shape",e,t,n))];default:throw TypeError("Node type ".concat(e.op," is not implemented"))}}(e,t,n)}));case"hash_table":return ql(e,t,n,a);case"custom":var s=Object(fl.a)(e.op);if(s&&s.customExecutor)return s.customExecutor(new dl(e,t,n));throw TypeError("Custom op ".concat(e.op," is not registered."));default:throw TypeError("Unknown op '".concat(e.op,"'. File an issue at ")+"https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()")}}(e,t,n);return i.wf.isPromise(s)?s.then((function(e){return[].concat(e)})):[].concat(s)}var ed=function(){function e(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{},n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{},a=arguments.length>3&&void 0!==arguments[3]?arguments[3]:{};Object(Yr.a)(this,e),this.weightMap=t,this.tensorArrayMap=n,this.tensorListMap=r,this.functionMap=a,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}return Object($r.a)(e,[{key:"newFrame",value:function(e,t){return{id:e,frameName:t,iterationId:0}}},{key:"currentContext",get:function(){return this.contexts},set:function(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}},{key:"currentContextId",get:function(){return this._currentContextIds[0]}},{key:"currentContextIds",get:function(){return this._currentContextIds}},{key:"generateCurrentContextIds",value:function(){for(var e=[],t=0;t<this.contexts.length-1;t++){var n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}e.push(""),this._currentContextIds=e}},{key:"contextIdforContexts",value:function(e){return e?e.map((function(e){return 0===e.id&&0===e.iterationId?"":"".concat(e.frameName,"-").concat(e.iterationId)})).join("/"):""}},{key:"enterFrame",value:function(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}},{key:"exitFrame",value:function(){if(!(this.contexts&&this.contexts.length>1))throw new Error("Cannot exit frame, the context is empty");this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift()}},{key:"nextIteration",value:function(){if(!(this.contexts&&this.contexts.length>0))throw new Error("Cannot increase frame iteration, the context is empty");this.contexts=this.contexts.slice(),this.lastId++;var e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}},{key:"getWeight",value:function(e){return this.weightMap[e]}},{key:"addTensorArray",value:function(e){this.tensorArrayMap[e.id]=e}},{key:"getTensorArray",value:function(e){return this.tensorArrayMap[e]}},{key:"addTensorList",value:function(e){this.tensorListMap[e.id]=e}},{key:"getTensorList",value:function(e){return this.tensorListMap[e]}},{key:"dispose",value:function(e){for(var t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(var n in this.tensorListMap)this.tensorListMap[n].clearAndClose(e)}}]),e}();function td(e,t,n,r){var a=new Set,i=[],o=null,s=null,c=new Set,u=Object.keys(e).map((function(e){return Object(ll.g)(e)[0]})),l=[];null!=r&&(l=r.map((function(e){return Object(ll.g)(e.name)[0]})));for(var d=Object(Vn.a)(t);d.length>0;){var f=d.pop();(id(f)||od(f)||sd(f))&&null==o&&(s=(o=f).children.map((function(e){return e.name})).filter((function(e){return a.has(e)}))),a.add(f.name),null==n[f.name]&&(-1===u.indexOf(f.name)&&-1===l.indexOf(f.name)&&(0!==f.inputs.length?f.inputs.forEach((function(e){c.has(e.name)||(c.add(e.name),d.push(e))})):i.push(f.name)))}return{inputs:e,outputs:t,usedNodes:a,missingInputs:i,dynamicNode:o,syncInputs:s}}var nd=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],rd=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],ad=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function id(e){return nd.indexOf(e.op)>=0}function od(e){return rd.indexOf(e.op)>=0}function sd(e){return ad.indexOf(e.op)>=0}var cd=function(){function e(t,n){var r=this;Object(Yr.a)(this,e),this.graph=t,this.parent=n,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this._outputs=t.outputs,this._inputs=t.inputs,this._initNodes=t.initNodes,this._signature=t.signature,this._functions=t.functions,null!=t.functions&&Object.keys(t.functions).forEach((function(n){r._functionExecutorMap[n]=new e(t.functions[n],r)}))}return Object($r.a)(e,[{key:"weightIds",get:function(){return this.parent?this.parent.weightIds:this._weightIds}},{key:"functionExecutorMap",get:function(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}},{key:"weightMap",get:function(){return this.parent?this.parent.weightMap:this._weightMap},set:function(e){var t,n=Object.keys(e).map((function(t){return e[t].map((function(e){return e.id}))}));this._weightIds=(t=[]).concat.apply(t,Object(Vn.a)(n)),this._weightMap=e}},{key:"resourceManager",set:function(e){this._resourceManager=e}},{key:"inputs",get:function(){return this._inputs.map((function(e){return{name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}}))}},{key:"outputs",get:function(){return this._outputs.map((function(e){return{name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}}))}},{key:"inputNodes",get:function(){return this._inputs.map((function(e){return e.signatureKey||e.name}))}},{key:"outputNodes",get:function(){return this._outputs.map((function(e){var t=e.signatureKey||e.name;return e.defaultOutput?"".concat(t,":").concat(e.defaultOutput):t}))}},{key:"functions",get:function(){var e=this;return Object.keys(this._functions).reduce((function(t,n){return t[n]=e._functions[n].signature,t}),{})}},{key:"getCompilationKey",value:function(e,t){var n=e.map((function(e){return e.name})).sort(),r=t.map((function(e){return e.name})).sort();return n.join(this.SEPERATOR)+"--"+r.join(this.SEPERATOR)}},{key:"compile",value:function(e,t){var n=td(e,t,this.weightMap,this._initNodes),r=n.missingInputs,a=n.dynamicNode,i=n.syncInputs;if(null!=a)throw new Error("This execution contains the node '".concat(a.name,"', which has ")+"the dynamic op '".concat(a.op,"'. Please use ")+"model.executeAsync() instead. Alternatively, to avoid the "+"dynamic ops, specify the inputs [".concat(i,"]"));if(r.length>0){var o=t.map((function(e){return e.name})),s=Object.keys(e);throw new Error("Cannot compute the outputs [".concat(o,"] from the provided inputs ")+"[".concat(s,"]. Missing the following inputs: [").concat(r,"]"))}return function(e,t,n){var r=n.usedNodes,a=n.inputs,i=[],o=Object.keys(a).map((function(e){return Object(ll.g)(e)[0]})).map((function(t){return e.nodes[t]})),s=e.initNodes;o.forEach((function(e){r.has(e.name)&&i.push(e)})),e.weights.forEach((function(e){r.has(e.name)&&i.push(e)})),null!=s&&s.forEach((function(e){r.has(e.name)&&i.push(e)}));for(var c=new Set,u=[];i.length>0;){var l=i.pop();c.add(l.name),t[l.name]||u.push(l),l.children.forEach((function(e){!c.has(e.name)&&r.has(e.name)&&e.inputs.every((function(e){return c.has(e.name)}))&&i.push(e)}))}return u}(this.graph,this.weightMap,n)}},{key:"execute",value:function(e,t){var n=this;e=this.mapInputs(e);var r=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);var a=r.map((function(e){return n.graph.nodes[Object(ll.g)(e)[0]]})),s=t.map((function(e){return Object(ll.g)(e)[0]})),c=s.map((function(e){return n.graph.nodes[e]}));0===c.length&&(c=this._outputs);var u=this.getCompilationKey(a,c),l=this.compiledMap.get(u);null==l&&(l=this.compile(e,c),this.compiledMap.set(u,l));var d={},f={};return Object(i.pf)((function(){var r=new ed(n.weightMap,d,f,n.functionExecutorMap),a=Object.assign({},n.weightMap);Object.keys(e).forEach((function(t){var n=Object(ll.g)(t),r=Object(o.a)(n,2),i=r[0],s=[];s[r[1]]=e[t],a[i]=s}));for(var c=n.getFrozenTensorIds(a),u={},p=0;p<l.length;p++){var h=l[p];if(!a[h.name]){var b=Jl(h,a,r,n._resourceManager);if(i.wf.isPromise(b))throw new Error("The execution of the op '".concat(h.op,"' returned a promise. ")+"Please use model.executeAsync() instead.");a[h.name]=b,n.checkTensorForDisposal(h.name,h,a,r,c,s,u)}}return null==n.parent&&r.dispose(c),t.map((function(e){return Object(ll.e)(e,a,r)}))}))}},{key:"getFrozenTensorIds",value:function(e){var t=[].concat.apply([],Object.keys(e).map((function(t){return e[t]})).map((function(e){return e.map((function(e){return e.id}))})));return new Set(t)}},{key:"checkTensorForDisposal",value:function(e,t,n,r,a,i,o){"control"!==t.category&&-1===i.indexOf(e)&&(n[e].forEach((function(e){null!=e&&(o[e.id]=(o[e.id]||0)+t.children.length)})),t.inputs.forEach((function(e){if("control"!==e.category){var t=Object(ll.f)(e.name,n,r);null!=t&&t.forEach((function(e){if(e&&!e.kept&&!a.has(e.id)){var t=o[e.id];1===t?(e.dispose(),delete o[e.id]):null!=t&&o[e.id]--}}))}})))}},{key:"executeAsync",value:function(){var e=Object(go.a)(vo.a.mark((function e(t,n){return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.abrupt("return",this._executeAsync(t,n));case 1:case"end":return e.stop()}}),e,this)})));return function(t,n){return e.apply(this,arguments)}}()},{key:"_executeAsync",value:function(){var e=Object(go.a)(vo.a.mark((function e(t,n){var r,a,i,o,s,c,u,l,d,f=arguments;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return r=f.length>2&&void 0!==f[2]&&f[2],a=f.length>3&&void 0!==f[3]?f[3]:{},i=f.length>4&&void 0!==f[4]?f[4]:{},r||(t=this.mapInputs(t),this.checkInputs(t),this.checkInputShapeAndType(t),n=this.mapOutputs(n),this.checkOutputs(n)),o=new ed(this.weightMap,a,i,this.functionExecutorMap),e.next=7,this.executeWithControlFlow(t,o,n,r);case 7:return s=e.sent,c=n.map((function(e){return Object(ll.e)(e,s,o)})),u=c.map((function(e){return e.id})),l=Object.keys(t).map((function(e){return t[e].id})),d=new Set([].concat(Object(Vn.a)(u),Object(Vn.a)(l),Object(Vn.a)(this.weightIds))),Object.keys(s).forEach((function(e){s[e].forEach((function(e){!e||e.kept||e.isDisposed||d.has(e.id)||e.dispose()}))})),null==this.parent&&o.dispose(d),e.abrupt("return",c);case 15:case"end":return e.stop()}}),e,this)})));return function(t,n){return e.apply(this,arguments)}}()},{key:"executeFunctionAsync",value:function(){var e=Object(go.a)(vo.a.mark((function e(t,n,r){var a,i=this;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return a=t.reduce((function(e,t,n){return e[i.inputs[n].name]=t,e}),{}),e.abrupt("return",this._executeAsync(a,this.outputNodes,!0,n,r));case 2:case"end":return e.stop()}}),e,this)})));return function(t,n,r){return e.apply(this,arguments)}}()},{key:"executeWithControlFlow",value:function(){var e=Object(go.a)(vo.a.mark((function e(t,n,r,a){var i,s,c,u,l,d,f,p,h,b,m,v,g,y,O,x,k,w=this;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:i=Object.keys(t),s=i.map((function(e){return w.graph.nodes[Object(ll.g)(e)[0]]})),c=r.map((function(e){return Object(ll.g)(e)[0]})),0===(u=c.map((function(e){return w.graph.nodes[e]}))).length&&(u=this._outputs),l=td(t,u,this.weightMap,this._initNodes),d=l.usedNodes,f=l.missingInputs,p=l.dynamicNode,h=l.syncInputs,b=[].concat(Object(Vn.a)(s),Object(Vn.a)(this.graph.weights),Object(Vn.a)(this._initNodes||[])).map((function(e){return{node:e,contexts:n.currentContext}})),m=Object.assign({},this.weightMap),Object.keys(t).forEach((function(e){var n=Object(ll.g)(e),r=Object(o.a)(n,2),a=r[0],i=[];i[r[1]]=t[e],m[a]=i})),v={},g=this.getFrozenTensorIds(m),y={};case 12:if(!(b.length>0)){e.next=18;break}return O=this.processStack(s,b,n,m,y,g,c,v,d),e.next=16,Promise.all(O);case 16:e.next=12;break;case 18:if(null!=p||a||console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead."),!((x=u.filter((function(e){return!id(e)&&!Object(ll.e)(e.name,m,n)})).map((function(e){return e.name}))).length>0)){e.next=24;break}throw k="",null!=p&&(k="Alternatively, to avoid the dynamic ops, use model.execute() "+"and specify the inputs [".concat(h,"]")),new Error("Cannot compute the outputs [".concat(x,"] from the provided ")+"inputs [".concat(i,"]. Consider providing the following inputs: ")+"[".concat(f,"]. ").concat(k));case 24:return e.abrupt("return",m);case 25:case"end":return e.stop()}}),e,this)})));return function(t,n,r,a){return e.apply(this,arguments)}}()},{key:"processStack",value:function(e,t,n,r,a,s,c,u,l){for(var d=this,f=[],p=function(){var e=t.pop();n.currentContext=e.contexts;var p="";if("Enter"===e.node.op&&Object(ll.d)("isConstant",e.node,r,n)){var h=Object(ll.b)(e.node.name,n),b=Object(o.a)(h,1);p=b[0]}if(null==r[e.node.name]){var m=Jl(e.node,r,n,d._resourceManager);if(!p){var v=Object(ll.b)(e.node.name,n),g=Object(o.a)(v,1);p=g[0]}var y=n.currentContext;i.wf.isPromise(m)?f.push(m.then((function(i){return r[p]=i,n.currentContext=y,d.checkTensorForDisposal(p,e.node,r,n,s,c,u),d.processChildNodes(e.node,t,n,r,a,l),i}))):(r[p]=m,d.checkTensorForDisposal(p,e.node,r,n,s,c,u),d.processChildNodes(e.node,t,n,r,a,l))}else d.processChildNodes(e.node,t,n,r,a,l)};t.length>0;)p();return f}},{key:"processChildNodes",value:function(e,t,n,r,a,i){e.children.forEach((function(e){var s=Object(ll.b)(e.name,n),c=Object(o.a)(s,1)[0];!a[c]&&i.has(e.name)&&("Merge"===e.op?e.inputNames.some((function(e){return!!Object(ll.e)(e,r,n)}))&&(a[c]=!0,t.push({contexts:n.currentContext,node:e})):e.inputNames.every((function(e){return!!Object(ll.e)(e,r,n)}))&&(a[c]=!0,t.push({contexts:n.currentContext,node:e})))}))}},{key:"dispose",value:function(){var e=this;Object.keys(this.weightMap).forEach((function(t){return e.weightMap[t].forEach((function(e){return e.dispose()}))}))}},{key:"checkInputShapeAndType",value:function(e){var t=this;Object.keys(e).forEach((function(n){var r=e[n],a=Object(ll.g)(n),s=Object(o.a)(a,1)[0],c=t.graph.nodes[s];if(c.attrParams.shape&&c.attrParams.shape.value){var u=c.attrParams.shape.value,l=u.length===r.shape.length&&r.shape.every((function(e,t){return-1===u[t]||u[t]===e}));i.wf.assert(l,(function(){return"The shape of dict['".concat(c.name,"'] provided in ")+"model.execute(dict) must be [".concat(u,"], but was ")+"[".concat(r.shape,"]")}))}c.attrParams.dtype&&c.attrParams.dtype.value&&i.wf.assert(r.dtype===c.attrParams.dtype.value,(function(){return"The dtype of dict['".concat(c.name,"'] provided in ")+"model.execute(dict) must be "+"".concat(c.attrParams.dtype.value,", but was ").concat(r.dtype)}))}))}},{key:"mapInputs",value:function(e){var t={};for(var n in e){if(null!=this._signature&&null!=this._signature.inputs&&null!=this._signature.inputs[n])t[this._signature.inputs[n].name]=e[n];else t[n]=e[n]}return t}},{key:"checkInputs",value:function(e){var t=this,n=Object.keys(e).filter((function(e){var n=Object(ll.g)(e),r=Object(o.a)(n,1)[0];return null==t.graph.nodes[r]}));if(n.length>0)throw new Error("The dict provided in model.execute(dict) has "+"keys: [".concat(n,"] that are not part of graph"))}},{key:"mapOutputs",value:function(e){var t=this;return e.map((function(e){return null!=t._signature&&null!=t._signature.outputs&&null!=t._signature.outputs[e]?t._signature.outputs[e].name:e}),{})}},{key:"checkOutputs",value:function(e){var t=this;e.forEach((function(e){var n=Object(ll.g)(e),r=Object(o.a)(n,1)[0];if(!t.graph.nodes[r])throw new Error("The output '".concat(e,"' is not found in the graph"))}))}}]),e}(),ud=function(){function e(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{},n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{};Object(Yr.a)(this,e),this.hashTableNameToHandle=t,this.hashTableMap=n}return Object($r.a)(e,[{key:"addHashTable",value:function(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}},{key:"getHashTableHandleByName",value:function(e){return this.hashTableNameToHandle[e]}},{key:"getHashTableById",value:function(e){return this.hashTableMap[e]}},{key:"dispose",value:function(){for(var e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(var t in this.hashTableNameToHandle)this.hashTableNameToHandle[t].dispose(),delete this.hashTableNameToHandle[t]}}]),e}(),ld="?tfjs-format=file",dd="model.json",fd=function(){function e(t){var n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{};Object(Yr.a)(this,e),this.modelUrl=t,this.loadOptions=n,this.version="n/a",null==n&&(this.loadOptions={}),this.resourceManager=new ud}return Object($r.a)(e,[{key:"modelVersion",get:function(){return this.version}},{key:"inputNodes",get:function(){return this.executor.inputNodes}},{key:"outputNodes",get:function(){return this.executor.outputNodes}},{key:"inputs",get:function(){return this.executor.inputs}},{key:"outputs",get:function(){return this.executor.outputs}},{key:"weights",get:function(){return this.executor.weightMap}},{key:"metadata",get:function(){return this.artifacts.userDefinedMetadata}},{key:"modelSignature",get:function(){return this.signature}},{key:"findIOHandler",value:function(){var e=this.modelUrl;if(null!=e.load)this.handler=e;else if(null!=this.loadOptions.requestInit)this.handler=i.ge.browserHTTPRequest(e,this.loadOptions);else{var t=i.ge.getLoadHandlers(e,this.loadOptions);if(0===t.length)t.push(i.ge.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error("Found more than one (".concat(t.length,") load handlers for ")+"URL '".concat([e],"'"));this.handler=t[0]}}},{key:"load",value:function(){var e=Object(go.a)(vo.a.mark((function e(){var t;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(this.findIOHandler(),null!=this.handler.load){e.next=3;break}throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");case 3:return e.next=5,this.handler.load();case 5:return t=e.sent,e.abrupt("return",this.loadSync(t));case 7:case"end":return e.stop()}}),e,this)})));return function(){return e.apply(this,arguments)}}()},{key:"loadSync",value:function(e){this.artifacts=e;var t,n=this.artifacts.modelTopology;t=null!=this.artifacts.userDefinedMetadata&&null!=this.artifacts.userDefinedMetadata.signature?this.artifacts.userDefinedMetadata.signature:this.artifacts.signature,this.signature=t,this.version="".concat(n.versions.producer,".").concat(n.versions.minConsumer);var r=i.ge.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new cd(ul.a.Instance.transformGraph(n,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,null!=e.modelInitializer&&null!=e.modelInitializer.node){var a=ul.a.Instance.transformGraph(e.modelInitializer);this.initializer=new cd(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}},{key:"save",value:function(){var e=Object(go.a)(vo.a.mark((function e(t,n){var r;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if("string"!==typeof t){e.next=9;break}if(0!==(r=i.ge.getSaveHandlers(t)).length){e.next=6;break}throw new Error("Cannot find any save handlers for URL '".concat(t,"'"));case 6:if(!(r.length>1)){e.next=8;break}throw new Error("Found more than one (".concat(r.length,") save handlers for ")+"URL '".concat(t,"'"));case 8:t=r[0];case 9:if(null!=t.save){e.next=11;break}throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");case 11:return e.abrupt("return",t.save(this.artifacts));case 12:case"end":return e.stop()}}),e,this)})));return function(t,n){return e.apply(this,arguments)}}()},{key:"predict",value:function(e,t){return this.execute(e,this.outputNodes)}},{key:"normalizeInputs",value:function(e){if(!(e instanceof i.bd)&&!Array.isArray(e))return e;if((e=Array.isArray(e)?e:[e]).length!==this.inputNodes.length)throw new Error("Input tensor count mismatch,"+"the graph model has ".concat(this.inputNodes.length," placeholders, ")+"while there are ".concat(e.length," input tensors."));return this.inputNodes.reduce((function(t,n,r){return t[n]=e[r],t}),{})}},{key:"normalizeOutputs",value:function(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}},{key:"execute",value:function(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);var n=this.executor.execute(e,t);return n.length>1?n:n[0]}},{key:"executeAsync",value:function(){var e=Object(go.a)(vo.a.mark((function e(t,n){var r;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return t=this.normalizeInputs(t),n=this.normalizeOutputs(n),e.next=4,this.executor.executeAsync(t,n);case 4:return r=e.sent,e.abrupt("return",r.length>1?r:r[0]);case 6:case"end":return e.stop()}}),e,this)})));return function(t,n){return e.apply(this,arguments)}}()},{key:"convertTensorMapToTensorsMap",value:function(e){return Object.keys(e).reduce((function(t,n){return t[n]=[e[n]],t}),{})}},{key:"dispose",value:function(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}}]),e}();function pd(e){return hd.apply(this,arguments)}function hd(){return(hd=Object(go.a)(vo.a.mark((function e(t){var n,r,a=arguments;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(n=a.length>1&&void 0!==a[1]?a[1]:{},null!=t){e.next=3;break}throw new Error("modelUrl in loadGraphModel() cannot be null. 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lf={kernelName:i.hc,backendName:"cpu",kernelFunc:uf},df=Zd(i.nc,(function(e){return Math.max(0,e)})),ff={kernelName:i.nc,backendName:"cpu",kernelFunc:df},pf=Zd(i.oc,(function(e){return Math.min(Math.max(0,e),6)})),hf={kernelName:i.oc,backendName:"cpu",kernelFunc:pf},bf=Zd(i.Bc,(function(e){return 1/(1+Math.exp(-e))})),mf={kernelName:i.Bc,backendName:"cpu",kernelFunc:bf};function vf(e,t,n,r,a){if("linear"===n)return nf({inputs:{x:t},backend:e});if("relu"===n)return df({inputs:{x:t},backend:e});if("elu"===n)return ef({inputs:{x:t},backend:e});if("relu6"===n)return pf({inputs:{x:t},backend:e});if("prelu"===n)return uf({inputs:{x:t,alpha:r},backend:e});if("leakyrelu"===n)return af({inputs:{x:t},backend:e,attrs:{alpha:a}});if("sigmoid"===n)return bf({inputs:{x:t},backend:e});throw new Error("Activation ".concat(n," has not been implemented for the CPU backend."))}function gf(e){var t=e.inputs,n=e.backend,r=t.real,a=t.imag,i=n.data.get(r.dataId).values,o=n.data.get(a.dataId).values,s=n.makeTensorInfo(r.shape,"complex64");return n.data.get(s.dataId).complexTensorInfos={real:n.makeTensorInfo(r.shape,"float32",i),imag:n.makeTensorInfo(a.shape,"float32",o)},s}var yf={kernelName:i.y,backendName:"cpu",kernelFunc:gf};function Of(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:"float32";if("complex64"===n){var r=Of(e,t,"float32"),a=Of(e,t,"float32");return gf({inputs:{real:r,imag:a},backend:e})}var o=i.wf.makeZerosTypedArray(i.wf.sizeFromShape(t),n);return e.makeTensorInfo(t,n,o)}function xf(e){var t=e.inputs,n=e.backend,r=t.input,a=n.data.get(r.dataId).complexTensorInfos.real,i=n.data.get(a.dataId).values;return n.makeTensorInfo(a.shape,a.dtype,i)}var kf={kernelName:i.kc,backendName:"cpu",kernelFunc:xf};function wf(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.dtype;if("complex64"===s){if("complex64"===a.dtype)return nf({inputs:{x:a},backend:n});var c=Of(n,a.shape,a.dtype),u=wf({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=gf({inputs:{real:u,imag:c},backend:n});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),l}if("complex64"===a.dtype){var d=xf({inputs:{input:a},backend:n}),f=wf({inputs:{x:d},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(d),f}if(!i.wf.hasEncodingLoss(a.dtype,s)){var p=nf({inputs:{x:a},backend:n});return{dataId:p.dataId,shape:p.shape,dtype:s}}if("int32"===s){var h=n.data.get(a.dataId).values,b=Int32Array.from(h);return n.makeTensorInfo(a.shape,"int32",b)}if("bool"===s){var m=n.data.get(a.dataId).values,v=i.wf.toTypedArray([0],a.dtype),g=sf((function(e,t){return e!==t?1:0}))(a.shape,[],m,v,"bool"),y=Object(o.a)(g,2),O=y[0],x=y[1];return n.makeTensorInfo(x,"bool",O)}throw new Error("Error in Cast: failed to cast ".concat(a.dtype," to ").concat(s))}var jf={kernelName:i.v,backendName:"cpu",kernelFunc:wf};function Sf(e,t,n,r){return null==n?function(n){var a=n.inputs,s=n.backend,c=a.a,u=a.b,l=s;Yd([c,u],e);var d=l.data.get(c.dataId).values,f=l.data.get(u.dataId).values,p="string"===c.dtype?i.ud.fromUint8ToStringArray(d):d,h="string"===c.dtype?i.ud.fromUint8ToStringArray(f):f,b=r||c.dtype,m=t(c.shape,u.shape,p,h,b),v=Object(o.a)(m,2),g=v[0],y=v[1];return l.makeTensorInfo(y,b,g)}:function(e){var a=e.inputs,i=e.backend,s=a.a,c=a.b,u=i;if("complex64"===s.dtype||"complex64"===c.dtype){var l=wf({inputs:{x:s},backend:u,attrs:{dtype:"complex64"}}),d=u.data.get(l.dataId),f=d.complexTensorInfos.real,p=d.complexTensorInfos.imag,h=u.data.get(f.dataId).values,b=u.data.get(p.dataId).values,m=wf({inputs:{x:c},backend:u,attrs:{dtype:"complex64"}}),v=u.data.get(m.dataId),g=v.complexTensorInfos.real,y=v.complexTensorInfos.imag,O=u.data.get(g.dataId).values,x=u.data.get(y.dataId).values,k=n(s.shape,c.shape,h,b,O,x),w=Object(o.a)(k,3),j=w[0],S=w[1],N=w[2],I=u.makeTensorInfo(N,"float32",j),C=u.makeTensorInfo(N,"float32",S),T=gf({inputs:{real:I,imag:C},backend:u});return u.disposeIntermediateTensorInfo(l),u.disposeIntermediateTensorInfo(m),u.disposeIntermediateTensorInfo(I),u.disposeIntermediateTensorInfo(C),T}var E=u.data.get(s.dataId).values,A=u.data.get(c.dataId).values,R=r||s.dtype,F=t(s.shape,c.shape,E,A,R),D=Object(o.a)(F,2),_=D[0],M=D[1];return u.makeTensorInfo(M,R,_)}}function Nf(e){return function(t,n,r,a,o,s){var c=i.ud.assertAndGetBroadcastShape(t,n),u=i.wf.sizeFromShape(c),l=c.length,d=i.wf.computeStrides(c),f=i.wf.getTypedArrayFromDType("float32",u),p=i.wf.getTypedArrayFromDType("float32",u),h=i.ud.getBroadcastDims(t,c),b=i.ud.getBroadcastDims(n,c),m=i.ud.mergeRealAndImagArrays(r,a),v=i.ud.mergeRealAndImagArrays(o,s),g=t.length,y=i.wf.computeStrides(t),O=n.length,x=i.wf.computeStrides(n);if(h.length+b.length===0)for(var k=0;k<f.length;k++){var w=k%m.length,j=k%v.length,S=e(m[2*w],m[2*w+1],v[2*j],v[2*j+1]);f[k]=S.real,p[k]=S.imag}else for(var N=function(t){var n=i.wf.indexToLoc(t,l,d),r=n.slice(-g);h.forEach((function(e){return r[e]=0}));var a=i.wf.locToIndex(r,g,y),o=n.slice(-O);b.forEach((function(e){return o[e]=0}));var s=i.wf.locToIndex(o,O,x),c=e(m[2*a],m[2*a+1],v[2*s],v[2*s+1]);f[t]=c.real,p[t]=c.imag},I=0;I<f.length;I++)N(I);return[f,p,c]}}var If=sf((function(e,t){return e+t})),Cf=Nf((function(e,t,n,r){return{real:e+n,imag:t+r}})),Tf=Sf(i.d,If,Cf),Ef={kernelName:i.d,backendName:"cpu",kernelFunc:Tf};function Af(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.shape,s=i.wf.sizeFromShape(a.shape),c=i.wf.inferFromImplicitShape(o,s),u=i.wf.sizeFromShape(c);i.wf.assert(s===u,(function(){return"The new shape (".concat(c,") has ").concat(u," elements and the old ")+"shape (".concat(a.shape,") has ").concat(s," elements. 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Y=0;Y<I;Y+=q)for(var $=0;$<S;$+=q)for(var Q=Math.min(X+q,N),Z=Math.min(Y+q,I),J=Math.min($+q,S),ee=X;ee<Q;ee++)for(var te=Y;te<Z;te++){for(var ne=0,re=$;re<J;re++){var ae=Math.min(K,g-1)*_,ie=Math.min(K,y-1)*U;ne+=T[ae+ee*M+re*z]*E[re*B+te*W+ie]}G[K*V+(ee*I+te)]+=ne}return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(j),n.makeTensorInfo(x,H.dtype,H.values)}var Df={kernelName:i.s,backendName:"cpu",kernelFunc:Ff};var _f={kernelName:i.ld,backendName:"cpu",kernelFunc:function(e){var t,n,r,a=e.inputs,i=e.backend,o=e.attrs,s=a.a,c=a.b,u=a.bias,l=a.preluActivationWeights,d=o.transposeA,f=o.transposeB,p=o.activation,h=o.leakyreluAlpha,b=[];t=Ff({inputs:{a:s,b:c},attrs:{transposeA:d,transposeB:f},backend:i}),u&&(n=Tf({inputs:{a:t,b:u},backend:i}),b.push(t),t=n),p&&(r=vf(i,t,p,l,h),b.push(t),t=r);for(var m=0,v=b;m<v.length;m++){var g=v[m];i.disposeIntermediateTensorInfo(g)}return t}};function Mf(e){for(var t=new Float32Array(e.length),n=0;n<e.length;++n)t[n]=Math.abs(e[n]);return t}var zf={kernelName:i.a,backendName:"cpu",kernelFunc:function(e){var t=e.inputs.x,n=e.backend;Yd(t,"abs");var r=new Float32Array(i.wf.sizeFromShape(t.shape));return r=Mf(n.data.get(t.dataId).values),n.makeOutput(r,t.shape,"float32")}},Lf=Zd(i.b,(function(e){return Math.acos(e)})),Pf={kernelName:i.b,backendName:"cpu",kernelFunc:Lf},Bf=Zd(i.c,(function(e){return Math.acosh(e)})),Wf={kernelName:i.c,backendName:"cpu",kernelFunc:Bf};var Uf={kernelName:i.e,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t;Yd(t,"addN");for(var a=r.map((function(e){return n.data.get(e.dataId).values})),o=Object(i.zd)(r[0].shape,r[0].dtype),s=o.values,c=0;c<r.length;c++)for(var u=a[c],l=0;l<s.length;l++)s[l]+=u[l];return n.makeTensorInfo(o.shape,o.dtype,o.values)}};function Vf(e,t,n,r,a){for(var o=t.length,s=i.wf.sizeFromShape(t),c=i.wf.computeStrides(t),u=i.wf.computeStrides(a),l=i.wf.getTypedArrayFromDType(n,i.wf.sizeFromShape(a)),d=0;d<s;++d){for(var f=i.wf.indexToLoc(d,o,c),p=new Array(f.length),h=0;h<p.length;h++)p[h]=f[r[h]];l[i.wf.locToIndex(p,o,u)]=e[d]}return l}function Hf(e){var t=e.inputs,n=e.attrs,r=e.backend,a=t.x,i=n.perm;Yd(a,"transpose");for(var o=a.shape.length,s=new Array(o),c=0;c<s.length;c++)s[c]=a.shape[i[c]];var u=Vf(r.data.get(a.dataId).values,a.shape,a.dtype,i,s);return{dataId:r.write(u,s,a.dtype),shape:s,dtype:a.dtype}}var Gf={kernelName:i.gd,backendName:"cpu",kernelFunc:Hf};var qf={kernelName:i.f,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.axis,c=r.keepDims;Yd(a,"all");var u=i.wf.parseAxisParam(s,a.shape),l=u,d=i.ud.getAxesPermutation(l,a.shape.length),f=a;null!=d&&(f=Hf({inputs:{x:a},backend:n,attrs:{perm:d}}),l=i.ud.getInnerMostAxes(l.length,a.shape.length)),i.ud.assertAxesAreInnerMostDims("all",l,f.shape.length);for(var p=i.ud.computeOutAndReduceShapes(f.shape,l),h=Object(o.a)(p,2),b=h[0],m=h[1],v=i.wf.sizeFromShape(m),g=i.wf.makeZerosTypedArray(i.wf.sizeFromShape(b),f.dtype),y=n.data.get(f.dataId).values,O=0;O<g.length;++O){for(var x=O*v,k=y[x],w=0;w<v;++w){var j=y[x+w];k=k&&j}g[O]=k}null!=d&&n.disposeIntermediateTensorInfo(f);var S=n.makeTensorInfo(b,f.dtype,g);if(c){var N=Af({inputs:{x:S},backend:n,attrs:{shape:i.ud.expandShapeToKeepDim(b,u)}});return n.disposeIntermediateTensorInfo(S),N}return S}};var Kf={kernelName:i.g,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.axis,c=r.keepDims;Yd(a,"any");var u=i.wf.parseAxisParam(s,a.shape),l=u,d=i.ud.getAxesPermutation(l,a.shape.length),f=a;null!=d&&(f=Hf({inputs:{x:a},backend:n,attrs:{perm:d}}),l=i.ud.getInnerMostAxes(l.length,a.shape.length)),i.ud.assertAxesAreInnerMostDims("any",l,f.shape.length);for(var p=i.ud.computeOutAndReduceShapes(f.shape,l),h=Object(o.a)(p,2),b=h[0],m=h[1],v=i.wf.sizeFromShape(m),g=i.wf.makeZerosTypedArray(i.wf.sizeFromShape(b),f.dtype),y=n.data.get(f.dataId).values,O=0;O<g.length;++O){for(var x=O*v,k=y[x],w=0;w<v;++w){var j=y[x+w];k=k||j}g[O]=k}null!=d&&n.disposeIntermediateTensorInfo(f);var S=n.makeTensorInfo(b,f.dtype,g);if(c){var N=Af({inputs:{x:S},backend:n,attrs:{shape:i.ud.expandShapeToKeepDim(b,u)}});return n.disposeIntermediateTensorInfo(S),N}return S}};var Xf={kernelName:i.h,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.axis;Yd(a,"argMax");var c=i.wf.parseAxisParam(s,a.shape),u=i.ud.getAxesPermutation(c,a.shape.length),l=a,d=[];null!=u&&(l=Hf({inputs:{x:a},backend:n,attrs:{perm:u}}),d.push(l),c=i.ud.getInnerMostAxes(c.length,l.shape.length)),c=[c[0]],i.ud.assertAxesAreInnerMostDims("argMax",c,l.shape.length);for(var f=i.ud.computeOutAndReduceShapes(l.shape,c),p=Object(o.a)(f,2),h=p[0],b=p[1],m=i.wf.sizeFromShape(h),v=i.wf.makeZerosTypedArray(m,"int32"),g=i.wf.sizeFromShape(b),y=n.data.get(l.dataId).values,O=0;O<v.length;++O){for(var x=O*g,k=y[x],w=0,j=0;j<g;++j){var S=y[x+j];S>k&&(k=S,w=j)}v[O]=w}return d.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),n.makeTensorInfo(h,"int32",v)}};var Yf={kernelName:i.i,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.axis;Yd(a,"argMin");var c=i.wf.parseAxisParam(s,a.shape),u=i.ud.getAxesPermutation(c,a.shape.length),l=a,d=[];null!=u&&(l=Hf({inputs:{x:a},backend:n,attrs:{perm:u}}),d.push(l),c=i.ud.getInnerMostAxes(c.length,l.shape.length)),c=[c[0]],i.ud.assertAxesAreInnerMostDims("argMin",c,l.shape.length);for(var f=i.ud.computeOutAndReduceShapes(l.shape,c),p=Object(o.a)(f,2),h=p[0],b=p[1],m=i.wf.sizeFromShape(h),v=i.wf.makeZerosTypedArray(m,"int32"),g=i.wf.sizeFromShape(b),y=n.data.get(l.dataId).values,O=0;O<v.length;++O){for(var x=O*g,k=y[x],w=0,j=0;j<g;++j){var S=y[x+j];S<k&&(k=S,w=j)}v[O]=w}return d.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),n.makeTensorInfo(h,"int32",v)}},$f=Zd(i.j,(function(e){return Math.asin(e)})),Qf={kernelName:i.j,backendName:"cpu",kernelFunc:$f},Zf=Zd(i.k,(function(e){return Math.asinh(e)})),Jf={kernelName:i.k,backendName:"cpu",kernelFunc:Zf},ep=Zd(i.l,(function(e){return Math.atan(e)})),tp={kernelName:i.l,backendName:"cpu",kernelFunc:ep},np=sf((function(e,t){return Math.atan2(e,t)})),rp=Sf(i.m,np),ap={kernelName:i.m,backendName:"cpu",kernelFunc:rp},ip=Zd(i.n,(function(e){return Math.atanh(e)})),op={kernelName:i.n,backendName:"cpu",kernelFunc:ip};function sp(e,t,n,r,a,o){for(var s=a.strideHeight,c=a.strideWidth,u=a.dilationHeight,l=a.dilationWidth,d=a.effectiveFilterHeight,f=a.effectiveFilterWidth,p=a.padInfo.top,h=a.padInfo.left,b="max"===o?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=Object(i.zd)(a.outShape,n),v=m.values,g=a.outShape[1]*a.outShape[2]*a.outShape[3],y=a.outShape[2]*a.outShape[3],O=a.outShape[3],x=0;x<a.batchSize;++x)for(var k=x*g,w=x*r[0],j=0;j<a.inChannels;++j)for(var S=0;S<a.outHeight;++S)for(var N=S*s-p,I=Math.max(0,N),C=Math.min(a.inHeight,d+N),T=k+S*y,E=0;E<a.outWidth;++E){for(var A=E*c-h,R=Math.max(0,A),F=Math.min(a.inWidth,f+A),D=b,_=0,M=0,z=I;z<C;z+=u){for(var L=w+z*r[1],P=R;P<F;P+=l){var B=e[L+P*r[2]+j];"max"===o&&B>D?D=B:"avg"===o&&(_+=B,M++)}if(isNaN(D))break}v[T+E*O+j]="avg"===o?_/M:D}return m}function cp(e,t,n,r){for(var a=arguments.length>4&&void 0!==arguments[4]&&arguments[4],o=arguments.length>5&&void 0!==arguments[5]&&arguments[5],s=Object(i.zd)(r.outShape,"int32"),c=r.strideHeight,u=r.strideWidth,l=r.dilationHeight,d=r.dilationWidth,f=r.effectiveFilterHeight,p=r.effectiveFilterWidth,h=r.padInfo.top,b=r.padInfo.left,m=Object(i.zd)(t,n,e),v=0;v<r.batchSize;++v)for(var g=0;g<r.inChannels;++g)for(var y=0;y<r.outHeight;++y){for(var O=y*c-h,x=O;x<0;)x+=l;for(var k=Math.min(r.inHeight,f+O),w=0;w<r.outWidth;++w){for(var j=w*u-b,S=j;S<0;)S+=d;for(var N=Math.min(r.inWidth,p+j),I=Number.NEGATIVE_INFINITY,C=-1,T=x;T<k;T+=l)for(var E=T-O,A=S;A<N;A+=d){var R=A-j,F=m.get(v,T,A,g);F>I&&(I=F,C=a?o?((v*r.inHeight+T)*r.inWidth+A)*r.inChannels+g:(T*r.inWidth+A)*r.inChannels+g:E*p+R)}s.set(C,v,y,w,g)}}return s}function up(e,t,n,r,a,o){for(var s=a.strideDepth,c=a.strideHeight,u=a.strideWidth,l=a.dilationDepth,d=a.dilationHeight,f=a.dilationWidth,p=a.effectiveFilterDepth,h=a.effectiveFilterHeight,b=a.effectiveFilterWidth,m=a.padInfo.front,v=a.padInfo.top,g=a.padInfo.left,y="max"===o?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,O=Object(i.zd)(a.outShape,n),x=O.values,k=a.outShape[1]*a.outShape[2]*a.outShape[3]*a.outShape[4],w=a.outShape[2]*a.outShape[3]*a.outShape[4],j=a.outShape[3]*a.outShape[4],S=a.outShape[4],N=0;N<a.batchSize;++N)for(var I=N*k,C=N*r[0],T=0;T<a.inChannels;++T)for(var E=0;E<a.outDepth;++E){for(var A=E*s-m,R=A;R<0;)R+=l;for(var F=Math.min(a.inDepth,p+A),D=I+E*w,_=0;_<a.outHeight;++_){for(var M=_*c-v,z=M;z<0;)z+=d;for(var L=Math.min(a.inHeight,h+M),P=D+_*j,B=0;B<a.outWidth;++B){for(var W=B*u-g,U=W;U<0;)U+=f;for(var V=Math.min(a.inWidth,b+W),H=P+B*S,G=y,q=0,K=0,X=R;X<F;X+=l){for(var Y=C+X*r[1],$=z;$<L;$+=d){for(var Q=Y+$*r[2],Z=U;Z<V;Z+=f){var J=e[Q+Z*r[3]+T];if("max"===o&&J>G?G=J:"avg"===o&&(q+=J,K++),isNaN(G))break}if(isNaN(G))break}if(isNaN(G))break}x[H+T]="avg"===o?q/K:G}}}return O}var lp={kernelName:i.o,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x;Yd(a,"avgPool");var o=r.filterSize,s=r.strides,c=r.pad,u=r.dimRoundingMode;i.wf.assert(i.ud.eitherStridesOrDilationsAreOne(s,1),(function(){return"Error in avgPool: Either strides or dilations must be 1. "+"Got strides ".concat(s," and dilations '").concat(1,"'")}));var l,d=i.ud.computePool2DInfo(a.shape,o,s,1,c,u);if(1===d.filterWidth&&1===d.filterHeight&&i.wf.arraysEqual(d.inShape,d.outShape))l=nf({inputs:{x:a},backend:n});else{var f=n.data.get(a.dataId).values,p=i.wf.computeStrides(a.shape),h=sp(f,a.shape,a.dtype,p,d,"avg");l=n.makeTensorInfo(d.outShape,a.dtype,h.values)}return l}};var dp={kernelName:i.p,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.filterSize,s=r.strides,c=r.pad,u=r.dimRoundingMode,l=r.dataFormat;Yd(a,"avgPool3d");var d=i.ud.computePool3DInfo(a.shape,o,s,1,c,u,l),f=up(n.data.get(a.dataId).values,a.shape,a.dtype,i.wf.computeStrides(a.shape),d,"avg");return n.makeTensorInfo(f.shape,"float32",f.values)}};var fp={kernelName:i.q,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,o=t.input,s=r.filterSize,c=r.strides,u=r.pad,l=r.dimRoundingMode;Yd([a,o],"avgPool3DGrad");for(var d=i.ud.computePool3DInfo(o.shape,s,c,1,u,l),f=d.strideDepth,p=d.strideHeight,h=d.strideWidth,b=d.filterDepth,m=d.filterHeight,v=d.filterWidth,g=d.dilationDepth,y=d.dilationHeight,O=d.dilationWidth,x=d.effectiveFilterDepth,k=d.effectiveFilterHeight,w=d.effectiveFilterWidth,j=x-1-d.padInfo.front,S=w-1-d.padInfo.left,N=k-1-d.padInfo.top,I=Object(i.zd)(o.shape,"float32"),C=1/(b*m*v),T=n.bufferSync(a),E=0;E<d.batchSize;++E)for(var A=0;A<d.inChannels;++A)for(var R=0;R<d.inDepth;++R)for(var F=0;F<d.inHeight;++F)for(var D=0;D<d.inWidth;++D){for(var _=R-j,M=F-N,z=D-S,L=0,P=0;P<x;P+=g){var B=(_+P)/f;if(!(B<0||B>=d.outDepth||Math.floor(B)!==B))for(var W=0;W<k;W+=y){var U=(M+W)/p;if(!(U<0||U>=d.outHeight||Math.floor(U)!==U))for(var V=0;V<w;V+=O){var H=(z+V)/h;if(!(H<0||H>=d.outWidth||Math.floor(H)!==H))L+=T.get(E,B,U,H,A)}}}I.set(L*C,E,R,F,D,A)}return n.makeTensorInfo(I.shape,I.dtype,I.values)}};var pp={kernelName:i.r,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,o=t.input,s=o;Yd([a,o],"avgPoolGrad");for(var c=r.filterSize,u=r.strides,l=r.pad,d=i.ud.computePool2DInfo(s.shape,c,u,1,l),f=d.strideHeight,p=d.strideWidth,h=d.filterHeight,b=d.filterWidth,m=d.dilationHeight,v=d.dilationWidth,g=d.effectiveFilterHeight,y=d.effectiveFilterWidth,O=y-1-d.padInfo.left,x=g-1-d.padInfo.top,k=Object(i.zd)(s.shape,"float32"),w=1/(h*b),j=n.data.get(a.dataId).values,S=Object(i.zd)(a.shape,"float32",j),N=0;N<d.batchSize;++N)for(var I=0;I<d.inChannels;++I)for(var C=0;C<d.inHeight;++C)for(var T=0;T<d.inWidth;++T){for(var E=C-x,A=T-O,R=0,F=0;F<g;F+=m){var D=(E+F)/f;if(!(D<0||D>=d.outHeight||Math.floor(D)!==D))for(var _=0;_<y;_+=v){var M=(A+_)/p;if(!(M<0||M>=d.outWidth||Math.floor(M)!==M))R+=S.get(N,D,M,I)}}k.set(R*w,N,C,T,I)}return n.makeTensorInfo(k.shape,k.dtype,k.values)}};var hp={kernelName:i.jb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.scale,s=t.offset,c=t.mean,u=t.variance;i.wf.assert(c.shape.length===u.shape.length,(function(){return"Batch normalization gradient requires mean and variance to have equal ranks."})),i.wf.assert(null==s||c.shape.length===s.shape.length,(function(){return"Batch normalization gradient requires mean and offset to have equal ranks."})),i.wf.assert(null==o||c.shape.length===o.shape.length,(function(){return"Batch normalization gradient requires mean and scale to have equal ranks."})),Yd([a,c,u,o,s],"batchNorm");var l=r.varianceEpsilon;null==l&&(l=.001);for(var d=n.data.get(a.dataId).values,f=n.data.get(c.dataId).values,p=n.data.get(u.dataId).values,h=o?n.data.get(o.dataId).values:new Float32Array([1]),b=s?n.data.get(s.dataId).values:new Float32Array([0]),m=new Float32Array(d.length),v=b.length,g=h.length,y=p.length,O=f.length,x=0,k=0,w=0,j=0,S=0;S<d.length;++S)m[S]=b[x++]+(d[S]-f[k++])*h[w++]/Math.sqrt(p[j++]+l),x>=v&&(x=0),k>=O&&(k=0),w>=g&&(w=0),j>=y&&(j=0);return n.makeTensorInfo(a.shape,a.dtype,m)}};function bp(e,t,n,r,a){var o=i.af.isSliceContinous(r,t,n),s=i.wf.sizeFromShape(n),c=i.wf.computeStrides(r);if(o){var u=i.af.computeFlatOffset(t,c);return"string"===a?e.slice(u,u+s):e.subarray(u,u+s)}for(var l="string"===a?i.ud.fromUint8ToStringArray(e):e,d=Object(i.zd)(r,a,l),f=Object(i.zd)(n,a),p=0;p<f.size;++p){var h=f.indexToLoc(p),b=h.map((function(e,n){return e+t[n]}));f.set.apply(f,[d.get.apply(d,Object(Vn.a)(b))].concat(Object(Vn.a)(h)))}return"string"===a?i.ud.fromStringArrayToUint8(f.values):f.values}function mp(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.begin,c=r.size;Yd(a,"slice");var u=i.af.parseSliceParams(a,s,c),l=Object(o.a)(u,2),d=l[0],f=l[1];i.af.assertParamsValid(a,d,f);var p=bp(n.data.get(a.dataId).values,d,f,a.shape,a.dtype);return n.makeTensorInfo(f,a.dtype,p)}var vp={kernelName:i.Fc,backendName:"cpu",kernelFunc:mp};var gp={kernelName:i.t,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.blockShape,s=r.crops;Yd([a],"batchToSpaceND");var c=o.reduce((function(e,t){return e*t})),u=i.ud.getReshaped(a.shape,o,c),l=i.ud.getPermuted(u.length,o.length),d=i.ud.getReshapedPermuted(a.shape,o,c),f=i.ud.getSliceBeginCoords(s,o.length),p=i.ud.getSliceSize(d,s,o.length),h=Af({inputs:{x:a},backend:n,attrs:{shape:u}}),b=Hf({inputs:{x:h},backend:n,attrs:{perm:l}}),m=Af({inputs:{x:b},backend:n,attrs:{shape:d}}),v=mp({inputs:{x:m},backend:n,attrs:{begin:f,size:p}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(m),v}};function yp(e,t,n,r,a){for(var o=i.wf.sizeFromShape(r),s=i.wf.makeZerosTypedArray(a,n),c=0;c<e.length;c++){var u=e[c];if(u<0)throw new Error("Input x must be non-negative!");u>=a||(s[u]+=o>0?t[c]:1)}return s}function Op(e,t,n){for(var r=arguments.length>3&&void 0!==arguments[3]&&arguments[3],a=e.shape[0],o=e.shape[1],s=Object(i.zd)([a,n],t.dtype),c=0;c<a;c++)for(var u=0;u<o;u++){var l=e.get(c,u);if(l<0)throw new Error("Input x must be non-negative!");l>=n||(r?s.set(1,c,l):t.size>0?s.set(s.get(c,l)+t.get(c,u),c,l):s.set(s.get(c,l)+1,c,l))}return s}var xp={kernelName:i.u,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.weights,o=r.size,s=yp(n.data.get(a.dataId).values,n.data.get(i.dataId).values,i.dtype,i.shape,o);return n.makeTensorInfo([o],i.dtype,s)}};function kp(e){return function(t,n,r){for(var a=i.wf.getTypedArrayFromDType(n,t.length),o=0;o<t.length;++o)a[o]=e(t[o],r);return a}}var wp=kp((function(e){return Math.ceil(e)})),jp=Jd(i.w,wp),Sp={kernelName:i.w,backendName:"cpu",kernelFunc:jp},Np=Zd(i.x,(function(e,t){var n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e})),Ip={kernelName:i.x,backendName:"cpu",kernelFunc:Np},Cp={kernelName:i.z,backendName:"cpu",kernelFunc:function(e){for(var t=e.inputs.x,n=e.backend,r=new Float32Array(i.wf.sizeFromShape(t.shape)),a=n.data.get(t.dataId),o=a.complexTensorInfos.real,s=a.complexTensorInfos.imag,c=n.data.get(o.dataId).values,u=n.data.get(s.dataId).values,l=0;l<c.length;l++){var d=c[l],f=u[l];r[l]=Math.hypot(d,f)}return n.makeOutput(r,t.shape,"float32")}};function Tp(e,t,n,r){var a=i.wf.getArrayFromDType(n,i.wf.sizeFromShape(t));if(r&&"string"!==n){var o=0;e.forEach((function(e){var t=i.wf.sizeFromShape(e.shape);a.set(e.vals,o),o+=t}))}else{var s=0;e.forEach((function(e){for(var r="string"===n?i.ud.fromUint8ToStringArray(e.vals):e.vals,o=0,c=0;c<e.shape[0];++c)for(var u=c*t[1]+s,l=0;l<e.shape[1];++l)a[u+l]=r[o++];s+=e.shape[1]}))}return a}function Ep(e){var t=e.inputs,n=e.backend,r=t.input,a=n.data.get(r.dataId).complexTensorInfos.imag,i=n.data.get(a.dataId).values;return n.makeTensorInfo(a.shape,a.dtype,i)}var Ap={kernelName:i.sb,backendName:"cpu",kernelFunc:Ep};function Rp(e){var t=e.inputs,n=e.backend,r=e.attrs.axis,a=i.wf.parseAxisParam(r,t[0].shape)[0],o=i.ud.computeOutShape(t.map((function(e){return e.shape})),a);if(0===i.wf.sizeFromShape(o))return n.makeTensorInfo(o,t[0].dtype,[]);var s=t.filter((function(e){return i.wf.sizeFromShape(e.shape)>0}));if(1===s.length)return nf({inputs:{x:s[0]},backend:n});var c=s.map((function(e){return e.shape}));if(i.ud.assertParamsConsistent(c,a),"complex64"===s[0].dtype){var u=s.map((function(e){return xf({inputs:{input:e},backend:n})})),l=s.map((function(e){return Ep({inputs:{input:e},backend:n})})),d=Rp({inputs:u,backend:n,attrs:{axis:a}}),f=Rp({inputs:l,backend:n,attrs:{axis:a}}),p=gf({inputs:{real:d,imag:f},backend:n});return u.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),l.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),p}var h=s.map((function(e){var t=i.wf.sizeFromShape(e.shape.slice(a));return Af({inputs:{x:e},backend:n,attrs:{shape:[-1,t]}})})),b=h.map((function(e){return{vals:n.data.get(e.dataId).values,shape:e.shape}}));o=i.ud.computeOutShape(h.map((function(e){return e.shape})),1);var m=1===h[0].shape[0],v=Tp(b,o,t[0].dtype,m),g=i.ud.computeOutShape(s.map((function(e){return e.shape})),a),y=n.makeTensorInfo(g,t[0].dtype,v);return h.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),y}var Fp={kernelName:i.A,backendName:"cpu",kernelFunc:Rp};function Dp(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.filter,s=r.strides,c=r.pad,u=r.dataFormat,l=r.dilations,d=r.dimRoundingMode;Yd([a,o],"conv2d");for(var f=i.ud.convertConv2DDataFormat(u),p=i.ud.computeConv2DInfo(a.shape,o.shape,s,l,c,d,!1,f),h=p.filterHeight,b=p.filterWidth,m=p.dilationHeight,v=p.dilationWidth,g=p.padInfo.left,y=p.padInfo.top,O="channelsLast"===p.dataFormat,x=new i.cd(p.outShape,a.dtype),k=i.wf.computeStrides(a.shape),w=i.wf.computeStrides(o.shape),j=k[0],S=O?k[1]:k[2],N=O?k[2]:1,I=O?1:k[1],C=x.strides[0],T=O?x.strides[1]:x.strides[2],E=O?x.strides[2]:1,A=O?1:x.strides[1],R=n.data.get(a.dataId).values,F=n.data.get(o.dataId).values,D=x.values,_=0;_<p.batchSize;++_)for(var M=_*j,z=_*C,L=0;L<p.outHeight;++L)for(var P=z+L*T,B=L*p.strideHeight-y,W=0;W<h;++W){var U=B+W*m;if(!(U<0||U>=p.inHeight))for(var V=W*w[0],H=M+U*S,G=0;G<p.outWidth;++G)for(var q=P+G*E,K=G*p.strideWidth-g,X=0;X<b;++X){var Y=K+X*v;if(!(Y<0||Y>=p.inWidth))for(var $=H+Y*N,Q=V+X*w[1],Z=0;Z<p.inChannels;++Z){for(var J=R[$+Z*I],ee=0;ee<p.outChannels;++ee)D[q+ee*A]+=J*F[Q+ee];Q+=p.outChannels}}}return n.makeTensorInfo(x.shape,x.dtype,D)}var _p={kernelName:i.B,backendName:"cpu",kernelFunc:Dp};var Mp={kernelName:i.C,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.dy,s=r.strides,c=r.pad,u=r.dataFormat,l=r.dimRoundingMode,d=r.filterShape;Yd([a,o],"conv2dBackpropFilter");for(var f=i.ud.convertConv2DDataFormat(u),p=i.ud.computeConv2DInfo(a.shape,d,s,1,c,l,!1,f),h=p.strideHeight,b=p.strideWidth,m=p.filterHeight,v=p.filterWidth,g="channelsLast"===p.dataFormat,y=new i.cd(p.filterShape,"float32"),O=p.padInfo.left,x=p.padInfo.top,k=n.data.get(a.dataId).values,w=n.data.get(o.dataId).values,j=new i.cd(a.shape,a.dtype,k),S=new i.cd(o.shape,o.dtype,w),N=0;N<m;++N)for(var I=Math.max(0,Math.ceil((x-N)/h)),C=Math.min(p.outHeight,(p.inHeight+x-N)/h),T=0;T<v;++T)for(var E=Math.max(0,Math.ceil((O-T)/b)),A=Math.min(p.outWidth,(p.inWidth+O-T)/b),R=0;R<p.inChannels;++R)for(var F=0;F<p.outChannels;++F){for(var D=0,_=0;_<p.batchSize;++_)for(var M=I;M<C;++M)for(var z=N+M*h-x,L=E;L<A;++L){var P=T+L*b-O;D+=g?j.get(_,z,P,R)*S.get(_,M,L,F):j.get(_,R,z,P)*S.get(_,F,M,L)}y.set(D,N,T,R,F)}return n.makeTensorInfo(y.shape,y.dtype,y.values)}};var zp={kernelName:i.D,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,s=t.filter,c=r.inputShape,u=r.strides,l=r.pad,d=r.dataFormat,f=r.dimRoundingMode;Yd([a,s],"conv2dBackpropInput");var p=i.wf.computeStrides(s.shape),h=i.wf.computeStrides(a.shape),b=i.ud.convertConv2DDataFormat(d),m=i.ud.computeConv2DInfo(c,s.shape,u,1,l,f,!1,b),v=new i.cd(m.inShape,"float32"),g=v.values,y=n.data.get(a.dataId).values,O=n.data.get(s.dataId).values,x=Object(o.a)(p,3),k=x[0],w=x[1],j=x[2],S=m.batchSize,N=m.filterHeight,I=m.filterWidth,C=m.inChannels,T=m.inHeight,E=m.inWidth,A=m.outChannels,R=m.outHeight,F=m.outWidth,D=m.strideHeight,_=m.strideWidth;b=m.dataFormat;for(var M=N-1-m.padInfo.top,z=I-1-m.padInfo.left,L="channelsLast"===b,P=v.strides[0],B=L?v.strides[1]:v.strides[2],W=L?v.strides[2]:1,U=L?1:v.strides[1],V=h[0],H=L?h[1]:h[2],G=L?h[2]:1,q=L?1:h[1],K=0;K<S;++K)for(var X=0;X<C;++X)for(var Y=0;Y<T;++Y)for(var $=Y-M,Q=Math.max(0,Math.ceil($/D)),Z=Math.min(R,(N+$)/D),J=0;J<E;++J){for(var ee=J-z,te=Math.max(0,Math.ceil(ee/_)),ne=Math.min(F,(I+ee)/_),re=0,ae=Q;ae<Z;++ae)for(var ie=ae*D-$,oe=te;oe<ne;++oe)for(var se=V*K+H*ae+G*oe,ce=k*(N-1-ie)+w*(I-1-(oe*_-ee))+j*X,ue=0;ue<A;++ue){re+=y[se+q*ue]*O[ce+ue]}g[P*K+B*Y+W*J+U*X]=re}return n.makeTensorInfo(v.shape,v.dtype,v.values)}};var Lp={kernelName:i.E,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.filter,s=r.strides,c=r.pad,u=r.dilations;Yd([a,o],"conv3d");for(var l=i.ud.computeConv3DInfo(a.shape,o.shape,s,u,c),d=l.filterDepth,f=l.filterHeight,p=l.filterWidth,h=l.dilationDepth,b=l.dilationHeight,m=l.dilationWidth,v=l.padInfo,g=v.front,y=v.left,O=v.top,x=new i.cd(l.outShape,a.dtype),k=n.data.get(a.dataId).values,w=n.data.get(o.dataId).values,j=x.values,S=i.wf.computeStrides(a.shape),N=i.wf.computeStrides(o.shape),I=0;I<l.batchSize;++I)for(var C=I*S[0],T=I*x.strides[0],E=0;E<l.outDepth;++E)for(var A=T+E*x.strides[1],R=E*l.strideDepth-g,F=0;F<d;++F){var D=R+F*h;if(!(D<0||D>=l.inDepth))for(var _=F*N[0],M=C+D*S[1],z=0;z<l.outHeight;++z)for(var L=A+z*x.strides[2],P=z*l.strideHeight-O,B=0;B<f;++B){var W=P+B*b;if(!(W<0||W>=l.inHeight))for(var U=_+B*N[1],V=M+W*S[2],H=0;H<l.outWidth;++H)for(var G=L+H*l.outChannels,q=H*l.strideWidth-y,K=0;K<p;++K){var X=q+K*m;if(!(X<0||X>=l.inWidth))for(var Y=U+K*N[2],$=V+X*l.inChannels,Q=Y,Z=0;Z<l.inChannels;++Z){for(var J=k[$+Z],ee=0;ee<l.outChannels;++ee)j[G+ee]+=J*w[Q+ee];Q+=l.outChannels}}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}};var Pp={kernelName:i.F,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=t.dy,c=r.strides,u=r.pad,l=r.filterShape;Yd([a,s],"conv3dBackpropFilterV2");for(var d=i.wf.computeStrides(a.shape),f=i.wf.computeStrides(s.shape),p=i.ud.computeConv3DInfo(a.shape,l,c,1,u),h=p.strideDepth,b=p.strideHeight,m=p.strideWidth,v=p.filterDepth,g=p.filterHeight,y=p.filterWidth,O=new i.cd(p.filterShape,"float32"),x=O.values,k=Object(o.a)(O.strides,4),w=k[0],j=k[1],S=k[2],N=k[3],I=n.data.get(s.dataId).values,C=Object(o.a)(f,4),T=C[0],E=C[1],A=C[2],R=C[3],F=n.data.get(a.dataId).values,D=Object(o.a)(d,4),_=D[0],M=D[1],z=D[2],L=D[3],P=p.padInfo.front,B=p.padInfo.left,W=p.padInfo.top,U=0;U<v;++U)for(var V=Math.max(0,Math.ceil((P-U)/h)),H=Math.min(p.outDepth,(p.inDepth+P-U)/h),G=U*w,q=0;q<g;++q)for(var K=Math.max(0,Math.ceil((W-q)/b)),X=Math.min(p.outHeight,(p.inHeight+W-q)/b),Y=q*j+G,$=0;$<y;++$)for(var Q=Math.max(0,Math.ceil((B-$)/m)),Z=Math.min(p.outWidth,(p.inWidth+B-$)/m),J=$*S+Y,ee=0;ee<p.inChannels;++ee)for(var te=ee*N+J,ne=0;ne<p.outChannels;++ne){for(var re=0,ae=0;ae<p.batchSize;++ae)for(var ie=ae*_,oe=ae*T,se=V;se<H;++se)for(var ce=(U+se*h-P)*M+ie,ue=se*E+oe,le=K;le<X;++le)for(var de=(q+le*b-W)*z+ce,fe=le*A+ue,pe=Q;pe<Z;++pe){var he=pe*R+fe;re+=F[($+pe*m-B)*L+de+ee]*I[he+ne]}x[te+ne]=re}return n.makeTensorInfo(O.shape,O.dtype,O.values)}};var Bp={kernelName:i.G,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,s=t.filter,c=r.pad,u=r.strides,l=r.inputShape;Yd([a],"conv3dBackpropInputV2");for(var d=i.wf.computeStrides(a.shape),f=i.wf.computeStrides(s.shape),p=i.ud.computeConv3DInfo(l,s.shape,u,1,c),h=new i.cd(p.inShape,"float32"),b=h.values,m=Object(o.a)(h.strides,4),v=m[0],g=m[1],y=m[2],O=m[3],x=n.data.get(a.dataId).values,k=Object(o.a)(d,4),w=k[0],j=k[1],S=k[2],N=k[3],I=n.data.get(s.dataId).values,C=Object(o.a)(f,4),T=C[0],E=C[1],A=C[2],R=C[3],F=p.batchSize,D=p.filterDepth,_=p.filterHeight,M=p.filterWidth,z=p.inChannels,L=p.inDepth,P=p.inHeight,B=p.inWidth,W=p.outChannels,U=p.outDepth,V=p.outHeight,H=p.outWidth,G=p.strideDepth,q=p.strideHeight,K=p.strideWidth,X=D-1-p.padInfo.front,Y=_-1-p.padInfo.top,$=M-1-p.padInfo.left,Q=0;Q<F;++Q)for(var Z=0;Z<z;++Z)for(var J=0;J<L;++J)for(var ee=J-X,te=Math.max(0,Math.ceil(ee/G)),ne=Math.min(U,(D+ee)/G),re=0;re<P;++re)for(var ae=re-Y,ie=Math.max(0,Math.ceil(ae/q)),oe=Math.min(V,(_+ae)/q),se=0;se<B;++se){for(var ce=se-$,ue=Math.max(0,Math.ceil(ce/K)),le=Math.min(H,(M+ce)/K),de=0,fe=te;fe<ne;++fe)for(var pe=fe*G-ee,he=ie;he<oe;++he)for(var be=he*q-ae,me=ue;me<le;++me)for(var 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D=y>1?(A-T)*(h-1)/(y-1):0,_=O>1?(R-E)*(b-1)/(O-1):0,M=0;M<y;M++){var z=y>1?T*(h-1)+M*D:.5*(T+A)*(h-1);if(z<0||z>h-1)for(var L=0;L<O;L++)for(var P=0;P<m;P++){var B=P+L*N[2]+M*N[1]+I*N[0];x.values[B]=d}else if("bilinear"===l)for(var W=Math.floor(z),U=Math.ceil(z),V=z-W,H=0;H<O;H++){var G=O>1?E*(b-1)+H*_:.5*(E+R)*(b-1);if(G<0||G>b-1)for(var q=0;q<m;q++){var K=q+H*N[2]+M*N[1]+I*N[0];x.values[K]=d}else for(var X=Math.floor(G),Y=Math.ceil(G),$=G-X,Q=0;Q<m;Q++){var Z=Q+X*S[2]+W*S[1]+F*S[0],J=j[Z],ee=j[Z=Q+Y*S[2]+W*S[1]+F*S[0]],te=j[Z=Q+X*S[2]+U*S[1]+F*S[0]],ne=J+(ee-J)*$,re=te+(j[Z=Q+Y*S[2]+U*S[1]+F*S[0]]-te)*$;Z=Q+H*N[2]+M*N[1]+I*N[0],x.values[Z]=ne+(re-ne)*V}}else for(var ae=0;ae<O;++ae){var ie=O>1?E*(b-1)+ae*_:.5*(E+R)*(b-1);if(ie<0||ie>b-1)for(var oe=0;oe<m;oe++){var se=oe+ae*N[2]+M*N[1]+I*N[0];x.values[se]=d}else for(var ce=Math.round(ie),ue=Math.round(z),le=0;le<m;le++){var de=le+ce*S[2]+ue*S[1]+F*S[0],fe=le+ae*N[2]+M*N[1]+I*N[0];x.values[fe]=j[de]}}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}};var qp={kernelName:i.K,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.axis,s=r.exclusive,c=r.reverse;Yd(a,"cumsum");var u=i.ud.getAxesPermutation([o],a.shape.length),l=a;null!=u&&(l=Hf({inputs:{x:a},backend:n,attrs:{perm:u}}));var d=i.ud.getInnerMostAxes(1,a.shape.length)[0];if(d!==l.shape.length-1)throw new Error("backend.cumsum in CPU expects an inner-most "+"axis=".concat(l.shape.length-1," but got axis=").concat(d));for(var f=Object(i.vf)(l.dtype,"int32"),p=i.wf.makeZerosTypedArray(i.wf.sizeFromShape(l.shape),f),h=n.data.get(l.dataId).values,b=l.shape[l.shape.length-1],m=c?function(e,t){return e+b-t-1}:function(e,t){return e+t},v=0;v<h.length;v+=b)for(var g=0;g<b;g++){var y=m(v,g);if(0===g)p[y]=s?0:h[y];else{var O=m(v,g-1);p[y]=s?h[O]+p[O]:h[y]+p[O]}}var x=n.makeTensorInfo(l.shape,f,p);if(null!=u){var k=Hf({inputs:{x:x},backend:n,attrs:{perm:i.ud.getUndoAxesPermutation(u)}});return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(l),k}return x}};var Kp={kernelName:i.M,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.weights,o=r.size,s=r.binaryOutput;if(1===a.shape.length){var c=yp(n.data.get(a.dataId).values,n.data.get(i.dataId).values,i.dtype,i.shape,o);return n.makeTensorInfo([o],i.dtype,c)}if(2===a.shape.length){var u=Op(n.bufferSync(a),n.bufferSync(i),o,s);return n.makeTensorInfo(u.shape,i.dtype,u.values)}throw new Error("Error in denseBincount: input must be at most rank 2, but got rank"+"".concat(a.shape.length,"."))}};var Xp={kernelName:i.N,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.blockSize,s=r.dataFormat;i.wf.assert("NHWC"===s,(function(){return"Only NHWC dataFormat supported on CPU for depthToSpace. Got ".concat(s)})),i.wf.assert(o>1,(function(){return"blockSize should be > 1 for depthToSpace, but was: ".concat(o)}));for(var c=a.shape[0],u=a.shape[1],l=a.shape[2],d=a.shape[3],f=u*o,p=l*o,h=d/(o*o),b=n.data.get(a.dataId).values,m=new Float32Array(c*f*p*h),v=0,g=0;g<c;++g)for(var y=0;y<f;++y)for(var O=Math.floor(y/o),x=y%o,k=0;k<p;++k)for(var w=Math.floor(k/o),j=(x*o+k%o)*h,S=0;S<h;++S){var N=S+j+d*(w+l*(O+u*g));m[v++]=b[N]}return n.makeTensorInfo([c,f,p,h],a.dtype,m)}};function Yp(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.filter,s=r.strides,c=r.pad,u=r.dilations,l=r.dimRoundingMode;Yd([a,o],"depthwiseConv2DNative");var d=i.wf.computeStrides(a.shape),f=i.wf.computeStrides(o.shape),p=u;null==p&&(p=[1,1]),i.wf.assert(i.ud.eitherStridesOrDilationsAreOne(s,p),(function(){return"Error in depthwiseConv2d: Either strides or dilations must be "+"1. Got strides ".concat(s," and dilations '").concat(p,"'")}));for(var h=i.ud.computeConv2DInfo(a.shape,o.shape,s,p,c,l,!0),b=h.filterHeight,m=h.filterWidth,v=h.dilationHeight,g=h.dilationWidth,y=h.padInfo,O=y.left,x=y.top,k=h.outChannels/h.inChannels,w=new i.cd(h.outShape,a.dtype),j=n.data.get(a.dataId).values,S=n.data.get(o.dataId).values,N=w.values,I=0;I<h.batchSize;++I)for(var C=I*d[0],T=I*w.strides[0],E=0;E<h.outHeight;++E)for(var A=T+E*w.strides[1],R=E*h.strideHeight-x,F=0;F<b;++F){var D=R+F*v;if(!(D<0||D>=h.inHeight))for(var _=F*f[0],M=C+D*d[1],z=0;z<h.outWidth;++z)for(var L=A+z*w.strides[2],P=z*h.strideWidth-O,B=0;B<m;++B){var W=P+B*g;if(!(W<0||W>=h.inWidth))for(var U=_+B*f[1],V=M+W*h.inChannels,H=L,G=U,q=0;q<h.inChannels;++q){for(var K=j[V+q],X=0;X<k;++X)N[H+X]+=K*S[G+X];H+=k,G+=k}}}return n.makeTensorInfo(w.shape,w.dtype,w.values)}var $p={kernelName:i.O,backendName:"cpu",kernelFunc:Yp};var Qp={kernelName:i.P,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.dy,s=r.strides,c=r.dilations,u=r.pad,l=r.dimRoundingMode,d=r.filterShape;Yd([a,o],"depthwiseConv2dNativeBackpropFilter");for(var f=i.ud.computeConv2DInfo(a.shape,d,s,c,u,l,!0),p=f.strideHeight,h=f.strideWidth,b=f.filterHeight,m=f.filterWidth,v=new i.cd(f.filterShape,"float32"),g=f.padInfo.left,y=f.padInfo.top,O=f.outChannels/f.inChannels,x=n.data.get(a.dataId).values,k=new i.cd(a.shape,a.dtype,x),w=n.data.get(o.dataId).values,j=new i.cd(o.shape,o.dtype,w),S=0;S<b;++S)for(var N=Math.max(0,Math.ceil((y-S)/p)),I=Math.min(f.outHeight,(f.inHeight+y-S)/p),C=0;C<m;++C)for(var T=Math.max(0,Math.ceil((g-C)/h)),E=Math.min(f.outWidth,(f.inWidth+g-C)/h),A=0;A<f.outChannels;++A){for(var R=Math.trunc(A/O),F=A%O,D=0,_=0;_<f.batchSize;++_)for(var M=N;M<I;++M)for(var z=S+M*p-y,L=T;L<E;++L){var P=C+L*h-g;D+=k.get(_,z,P,R)*j.get(_,M,L,A)}v.set(D,S,C,R,F)}return n.makeTensorInfo(v.shape,v.dtype,v.values)}};var Zp={kernelName:i.Q,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,s=t.filter,c=r.strides,u=r.dilations,l=r.pad,d=r.dimRoundingMode,f=r.inputShape;Yd([a,s],"depthwiseConv2DNativeBackpropInput");for(var p=i.wf.computeStrides(a.shape),h=i.wf.computeStrides(s.shape),b=i.ud.computeConv2DInfo(f,s.shape,c,u,l,d,!0),m=new i.cd(b.inShape,"float32"),v=m.values,g=Object(o.a)(m.strides,3),y=g[0],O=g[1],x=g[2],k=n.data.get(a.dataId).values,w=Object(o.a)(p,3),j=w[0],S=w[1],N=w[2],I=n.data.get(s.dataId).values,C=Object(o.a)(h,3),T=C[0],E=C[1],A=C[2],R=b.batchSize,F=b.filterHeight,D=b.filterWidth,_=b.inChannels,M=b.inHeight,z=b.inWidth,L=b.outChannels,P=b.outHeight,B=b.outWidth,W=b.strideHeight,U=b.strideWidth,V=F-1-b.padInfo.top,H=D-1-b.padInfo.left,G=L/_,q=0;q<R;++q)for(var K=0;K<_;++K)for(var X=0;X<M;++X)for(var Y=X-V,$=Math.max(0,Math.ceil(Y/W)),Q=Math.min(P,(F+Y)/W),Z=0;Z<z;++Z){for(var 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t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.filter,s=r.strides,c=r.pad,u=r.dilations,l=n,d=l.data.get(a.dataId).values,f=a.shape.length,p=l.data.get(o.dataId).values,h=o.shape.length,b=i.ud.computeDilation2DInfo(a.shape,o.shape,s,c,"NHWC",u),m=b.batchSize,v=b.inHeight,g=b.inWidth,y=b.inChannels,O=b.outHeight,x=b.outWidth,k=b.padInfo,w=b.strideHeight,j=b.strideWidth,S=b.filterHeight,N=b.filterWidth,I=b.dilationHeight,C=b.dilationWidth,T=b.outShape,E=i.wf.sizeFromShape(T),A=T.length,R=i.wf.getArrayFromDType(a.dtype,E),F=0;F<m;++F)for(var D=0;D<O;++D)for(var _=D*w-k.top,M=0;M<x;++M)for(var z=M*j-k.left,L=0;L<y;++L){for(var P=Number.MIN_SAFE_INTEGER,B=0;B<S;++B){var W=_+B*I;if(W>=0&&W<v)for(var U=0;U<N;++U){var V=z+U*C;if(V>=0&&V<g){var 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b=i.ud.computeOutAndReduceShapes(h.shape,p),m=Object(o.a)(b,2),v=m[0],g=m[1],y=Of(r,v,i.ud.upcastType(h.dtype,"int32")),O=i.wf.sizeFromShape(g),x=r.data.get(y.dataId).values,k=r.data.get(h.dataId).values,w=0;w<x.length;++w){for(var j=w*O,S=0,N=0;N<O;++N)S+=k[j+N];x[w]=S}if(u){var I=y;y=Af({inputs:{x:y},backend:r,attrs:{shape:i.ud.expandShapeToKeepDim(y.shape,d)}}),r.disposeIntermediateTensorInfo(I)}return r.disposeIntermediateTensorInfo(t),null!=f&&r.disposeIntermediateTensorInfo(h),y}var ch={kernelName:i.Yc,backendName:"cpu",kernelFunc:sh};var uh={kernelName:i.V,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs.equation,a=t,o=i.ud.decodeEinsumEquation(r,a.length),s=o.allDims,c=o.summedDims,u=o.idDims;i.ud.checkEinsumDimSizes(s.length,u,a);for(var l=i.ud.getEinsumComputePath(c,u),d=l.path,f=l.steps,p=f.length,h=null,b=s.length,m=[],v=0;v<p;++v){var g,y=Object(ea.a)(f[v]);try{for(y.s();!(g=y.n()).done;){var 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l=a.shape[3],d=l-1,f=n.data.get(a.dataId).values,p=i.wf.sizeFromShape(a.shape),h=new Float32Array(p);function b(e){for(var t=e%l,n=e-t+Math.max(0,t-o),r=e-t+Math.min(t+o,d),a=0;n<=r;n++){var i=f[n];a+=i*i}return a}for(var m=0;m<p;m++){var v=b(m),g=f[m]*Math.pow(s+c*v,-u);h[m]=g}return n.makeTensorInfo(a.shape,a.dtype,h)}};var zb={kernelName:i.yb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.y,s=t.dy,c=r.depthRadius,u=r.bias,l=r.alpha,d=r.beta;Yd(s,"LRNGrad");for(var f=i.wf.sizeFromShape(s.shape),p=s.shape[3],h=n.data.get(s.dataId).values,b=n.data.get(a.dataId).values,m=n.data.get(o.dataId).values,v=new Float32Array(f),g=f,y=0;y<g;y++){for(var O=y%p,x=y-O+Math.max(0,O-c),k=y-O+Math.min(p,O+c+1),w=0,j=x;j<k;j++)w+=Math.pow(b[j],2);w=l*w+u;for(var S=x;S<k;S++){var N=-2*l*d*b[S]*m[y]/w;y===S&&(N+=Math.pow(w,-d)),N*=h[y],v[S]+=N}}return n.makeTensorInfo(s.shape,a.dtype,v)}};function Lb(e,t,n,r){for(var a=i.wf.getTypedArrayFromDType(r,i.wf.sizeFromShape(n)),o=0;o<a.length;++o){for(var s=o*t,c=e[s],u=0;u<t;++u){var l=e[s+u];(Number.isNaN(l)||l>c)&&(c=l)}a[o]=c}return a}function Pb(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.reductionIndices,c=r.keepDims,u=n,l=a.shape,d=l.length,f=i.wf.parseAxisParam(s,l),p=f,h=i.ud.getAxesPermutation(p,d),b=u.data.get(a.dataId).values;if(null!=h){for(var m=new Array(d),v=0;v<m.length;v++)m[v]=l[h[v]];b=Vf(b,l,a.dtype,h,m),p=i.ud.getInnerMostAxes(p.length,d),l=m}Yd(a,"max"),i.ud.assertAxesAreInnerMostDims("max",p,d);var g=i.ud.computeOutAndReduceShapes(l,p),y=Object(o.a)(g,2),O=y[0],x=y[1],k=Lb(b,i.wf.sizeFromShape(x),O,a.dtype),w=u.write(k,O,a.dtype),j=O;c&&(j=i.ud.expandShapeToKeepDim(O,f));return{dataId:w,shape:j,dtype:a.dtype}}var Bb={kernelName:i.Ib,backendName:"cpu",kernelFunc:Pb},Wb=sf((function(e,t){return Math.max(e,t)})),Ub=Sf(i.Ob,Wb),Vb={kernelName:i.Ob,backendName:"cpu",kernelFunc:Ub};var Hb={kernelName:i.Jb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x;Yd(a,"maxPool");var o=r.filterSize,s=r.strides,c=r.pad,u=r.dimRoundingMode;i.wf.assert(i.ud.eitherStridesOrDilationsAreOne(s,1),(function(){return"Error in maxPool: Either strides or dilations must be 1. 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n}(n.bufferSync(o),d),p=d.strideDepth,h=d.strideHeight,b=d.strideWidth,m=d.dilationDepth,v=d.dilationHeight,g=d.dilationWidth,y=d.effectiveFilterDepth,O=d.effectiveFilterHeight,x=d.effectiveFilterWidth,k=y-1-d.padInfo.front,w=x-1-d.padInfo.left,j=O-1-d.padInfo.top,S=Object(i.zd)(o.shape,"float32"),N=n.bufferSync(a),I=0;I<d.batchSize;++I)for(var C=0;C<d.inChannels;++C)for(var T=0;T<d.inDepth;++T)for(var E=0;E<d.inHeight;++E)for(var A=0;A<d.inWidth;++A){for(var R=T-k,F=E-j,D=A-w,_=0,M=0;M<y;M+=m){var z=(R+M)/p;if(!(z<0||z>=d.outDepth||Math.floor(z)!==z))for(var L=0;L<O;L+=v){var P=(F+L)/h;if(!(P<0||P>=d.outHeight||Math.floor(P)!==P))for(var B=0;B<x;B+=g){var W=(D+B)/b;if(!(W<0||W>=d.outWidth||Math.floor(W)!==W)){var U=y*O*x-1-f.get(I,z,P,W,C)===M*O*x+L*x+B?1:0;if(0!==U)_+=N.get(I,z,P,W,C)*U}}}}S.set(_,I,T,E,A,C)}return n.makeTensorInfo(S.shape,S.dtype,S.values)}};var Kb={kernelName:i.Mb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,o=t.input,s=o;Yd([o,t.output],"maxPoolGrad");for(var c=r.filterSize,u=r.strides,l=r.pad,d=r.dimRoundingMode,f=i.ud.computePool2DInfo(s.shape,c,u,1,l,d),p=n.data.get(s.dataId).values,h=Object(i.zd)(f.outShape,s.dtype,cp(p,s.shape,s.dtype,f).values),b=f.strideHeight,m=f.strideWidth,v=f.dilationHeight,g=f.dilationWidth,y=f.effectiveFilterHeight,O=f.effectiveFilterWidth,x=O-1-f.padInfo.left,k=y-1-f.padInfo.top,w=Object(i.zd)(s.shape,"float32"),j=n.data.get(a.dataId).values,S=Object(i.zd)(a.shape,"float32",j),N=0;N<f.batchSize;++N)for(var I=0;I<f.inChannels;++I)for(var C=0;C<f.inHeight;++C)for(var T=0;T<f.inWidth;++T){for(var E=C-k,A=T-x,R=0,F=0;F<y;F+=v){var D=(E+F)/b;if(!(D<0||D>=f.outHeight||Math.floor(D)!==D))for(var _=0;_<O;_+=g){var M=(A+_)/m;if(!(M<0||M>=f.outWidth||Math.floor(M)!==M)){var z=y*O-1-h.get(N,D,M,I)===F*O+_?1:0;if(0!==z)R+=S.get(N,D,M,I)*z}}}w.set(R,N,C,T,I)}return n.makeTensorInfo(w.shape,w.dtype,w.values)}};var Xb={kernelName:i.Nb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.attrs,r=e.backend,a=t.x,s=n.filterSize,c=n.strides,u=n.pad,l=n.includeBatchInIndex,d=r;Yd(a,"MaxPoolWithArgmax");var f=d.data.get(a.dataId).values,p=i.ud.computePool2DInfo(a.shape,s,c,[1,1],u),h=function(e,t,n,r,a){var o=sp(e,0,n,i.wf.computeStrides(t),a,"max"),s=cp(e,t,n,a,!0,r);return[o.values,s.values]}(f,a.shape,a.dtype,l,p),b=Object(o.a)(h,2),m=b[0],v=b[1],g=d.write(m,p.outShape,a.dtype),y=d.write(v,p.outShape,a.dtype);return[{dataId:g,shape:p.outShape,dtype:a.dtype},{dataId:y,shape:p.outShape,dtype:"int32"}]}};var Yb={kernelName:i.Pb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.axis,s=r.keepDims,c=i.wf.parseAxisParam(o,a.shape),u=i.ud.computeOutAndReduceShapes(a.shape,c)[1],l=i.wf.sizeFromShape(u),d=[],f=n.makeTensorInfo([],"float32",new Float32Array([l]));d.push(f);var p=wf({inputs:{x:a},backend:n,attrs:{dtype:"float32"}});d.push(p);var h=Ah({inputs:{a:p,b:f},backend:n});d.push(h);var b=sh({inputs:{x:h},backend:n,attrs:{axis:o,keepDims:s}});return d.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),b}};var $b={kernelName:i.Qb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.axis,c=r.keepDims;Yd(a,"min");var u=i.wf.parseAxisParam(s,a.shape),l=u,d=i.ud.getAxesPermutation(l,a.shape.length),f=a;null!=d&&(f=Hf({inputs:{x:a},backend:n,attrs:{perm:d}}),l=i.ud.getInnerMostAxes(l.length,a.shape.length)),i.ud.assertAxesAreInnerMostDims("min",l,f.shape.length);for(var p=i.ud.computeOutAndReduceShapes(f.shape,l),h=Object(o.a)(p,2),b=h[0],m=h[1],v=i.wf.sizeFromShape(m),g=i.wf.makeZerosTypedArray(i.wf.sizeFromShape(b),f.dtype),y=n.data.get(f.dataId).values,O=0;O<g.length;++O){for(var x=O*v,k=y[x],w=0;w<v;++w){var j=y[x+w];(Number.isNaN(j)||j<k)&&(k=j)}g[O]=k}null!=d&&n.disposeIntermediateTensorInfo(f);var S=n.makeTensorInfo(b,f.dtype,g);if(c){var 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u=c?a:am({inputs:{logits:a},backend:n,attrs:{dim:-1}}),l=u.shape[0],d=u.shape[1],f=n.data.get(u.dataId).values,p=[l,o],h=i.wf.makeZerosTypedArray(i.wf.sizeFromShape(p),"int32"),b=0;b<l;++b){var m=b*d,v=new Float32Array(d-1);v[0]=f[m];for(var g=1;g<v.length;++g)v[g]=v[g-1]+f[m+g];for(var y=bd.alea(s.toString()),O=b*o,x=0;x<o;++x){var k=y();h[O+x]=v.length;for(var w=0;w<v.length;w++)if(k<v[w]){h[O+x]=w;break}}}return c||n.disposeIntermediateTensorInfo(u),n.makeTensorInfo(p,"int32",h)}};function sm(e,t,n){var r=i.wf.createScalarValue(-1,n);return rh([],t,r,e,n)}var cm={kernelName:i.Wb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.x;Yd(r,"neg");var a=sm(n.data.get(r.dataId).values,r.shape,r.dtype),i=Object(o.a)(a,2),s=i[0],c=i[1];return n.makeTensorInfo(c,r.dtype,s)}},um=i.ie.nonMaxSuppressionV3Impl;var lm={kernelName:i.Xb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.boxes,i=t.scores,o=r.maxOutputSize,s=r.iouThreshold,c=r.scoreThreshold;Yd(a,"NonMaxSuppression");var u=n.data.get(a.dataId).values,l=n.data.get(i.dataId).values,d=um(u,l,o,s,c).selectedIndices;return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}},dm=i.ie.nonMaxSuppressionV4Impl;var fm={kernelName:i.Yb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.boxes,i=t.scores,o=r.maxOutputSize,s=r.iouThreshold,c=r.scoreThreshold,u=r.padToMaxOutputSize;Yd(a,"NonMaxSuppressionPadded");var l=n.data.get(a.dataId).values,d=n.data.get(i.dataId).values,f=dm(l,d,o,s,c,u),p=f.selectedIndices,h=f.validOutputs;return[n.makeTensorInfo([p.length],"int32",new Int32Array(p)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}},pm=i.ie.nonMaxSuppressionV5Impl;var hm={kernelName:i.Zb,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.boxes,i=t.scores,o=r.maxOutputSize,s=r.iouThreshold,c=r.scoreThreshold,u=r.softNmsSigma;Yd(a,"NonMaxSuppressionWithScore");var l=n.data.get(a.dataId).values,d=n.data.get(i.dataId).values,f=pm(l,d,o,s,c,u),p=f.selectedIndices,h=f.selectedScores;return[n.makeTensorInfo([p.length],"int32",new Int32Array(p)),n.makeTensorInfo([h.length],"float32",new Float32Array(h))]}},bm=sf((function(e,t){return e!==t?1:0})),mm=Sf(i.ac,bm,null,"bool"),vm={kernelName:i.ac,backendName:"cpu",kernelFunc:mm};var gm={kernelName:i.bc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.indices,o=r.depth,s=r.onValue,c=r.offValue;Yd(a,"oneHot");var u=i.wf.sizeFromShape(a.shape),l=new Float32Array(u*o);l.fill(c);for(var d=n.data.get(a.dataId).values,f=0;f<u;++f)d[f]>=0&&d[f]<o&&(l[f*o+d[f]]=s);return n.makeTensorInfo([].concat(Object(Vn.a)(a.shape),[o]),"int32",l)}};function ym(e){var t=e.inputs,n=e.backend,r=t.x;if("string"===r.dtype)throw new Error("zerosLike is not supported for string tensors");if("complex64"===r.dtype){var a=xf({inputs:{input:r},backend:n}),i=ym({inputs:{x:a},backend:n}),o=Ep({inputs:{input:r},backend:n}),s=ym({inputs:{x:o},backend:n}),c=gf({inputs:{real:i,imag:s},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(s),c}return Wh({backend:n,attrs:{shape:r.shape,value:0,dtype:r.dtype}})}var Om={kernelName:i.kd,backendName:"cpu",kernelFunc:ym};var xm={kernelName:i.cc,backendName:"cpu",kernelFunc:function e(t){var n=t.inputs,r=t.backend,a=n.x;if("string"===a.dtype)throw new Error("onesLike is not supported for string tensors");if("complex64"===a.dtype){var i=xf({inputs:{input:a},backend:r}),o=e({inputs:{x:i},backend:r}),s=Ep({inputs:{input:a},backend:r}),c=ym({inputs:{x:s},backend:r}),u=gf({inputs:{real:o,imag:c},backend:r});return 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t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.paddings,s=r.constantValue;Yd(a,"pad");var c=o.map((function(e,t){return e[0]+a.shape[t]+e[1]})),u=o.map((function(e){return e[0]})),l=n.data.get(a.dataId).values,d=i.wf.sizeFromShape(a.shape),f=a.shape.length,p=i.wf.computeStrides(a.shape),h=i.wf.sizeFromShape(c),b=c.length,m=i.wf.computeStrides(c),v=i.wf.getTypedArrayFromDType(a.dtype,h);0!==s&&v.fill(s);for(var g=0;g<d;g++){var y=i.wf.indexToLoc(g,f,p).map((function(e,t){return e+u[t]}));v[i.wf.locToIndex(y,b,m)]=l[g]}return{dataId:n.write(v,c,a.dtype),shape:c,dtype:a.dtype}}},Sm=sf((function(e,t){return Math.pow(e,t)})),Nm=Sf(i.gc,Sm),Im={kernelName:i.gc,backendName:"cpu",kernelFunc:Nm};function Cm(e,t,n,r){for(var a=i.ud.computeOutAndReduceShapes(e,r),s=Object(o.a)(a,2),c=s[0],u=s[1],l=Object(i.vf)(t,"int32"),d=i.wf.makeZerosTypedArray(i.wf.sizeFromShape(c),l),f=i.wf.sizeFromShape(u),p=0;p<d.length;++p){for(var 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t=e.backend,n=e.attrs,r=n.start,a=n.stop,i=n.dtype,o=Em(r,a,n.step,i);return t.makeTensorInfo([o.length],i,o)}},Rm=Zd(i.mc,(function(e){return 1/e})),Fm={kernelName:i.mc,backendName:"cpu",kernelFunc:Rm};var Dm={kernelName:i.qc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,s=r.alignCorners,c=r.halfPixelCenters,u=r.size;Yd(a,"resizeBilinear");for(var l=i.wf.computeStrides(a.shape),d=Object(o.a)(u,2),f=d[0],p=d[1],h=Object(o.a)(a.shape,4),b=h[0],m=h[1],v=h[2],g=h[3],y=n.data.get(a.dataId).values,O=new Float32Array(i.wf.sizeFromShape([b,f,p,g])),x=[s&&f>1?m-1:m,s&&p>1?v-1:v],k=[s&&f>1?f-1:f,s&&p>1?p-1:p],w=0,j=x[0]/k[0],S=x[1]/k[1],N=0;N<b;N++)for(var I=0;I<f;I++){var C=void 0;C=c?j*(I+.5)-.5:j*I;for(var T=Math.max(0,Math.floor(C)),E=C-T,A=Math.min(m-1,Math.ceil(C)),R=N*l[0]+T*l[1],F=N*l[0]+A*l[1],D=0;D<p;D++){var _=void 0;_=c?S*(D+.5)-.5:S*D;for(var M=Math.max(0,Math.floor(_)),z=_-M,L=Math.min(v-1,Math.ceil(_)),P=R+M*l[2],B=F+M*l[2],W=R+L*l[2],U=F+L*l[2],V=0;V<g;V++){var H=y[P+V],G=y[B+V],q=H+(y[W+V]-H)*z,K=q+(G+(y[U+V]-G)*z-q)*E;O[w++]=K}}}return n.makeTensorInfo([b,f,p,g],"float32",O)}};var _m={kernelName:i.rc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,s=t.dy,c=r.alignCorners;Yd([s,a],"resizeBilinearGrad");for(var u=i.wf.computeStrides(a.shape),l=Object(o.a)(a.shape,4),d=l[0],f=l[1],p=l[2],h=l[3],b=Object(o.a)(s.shape,3),m=b[1],v=b[2],g=new Float32Array(d*f*p*h),y=[c&&m>1?f-1:f,c&&v>1?p-1:p],O=[c&&m>1?m-1:m,c&&v>1?v-1:v],x=y[0]/O[0],k=y[1]/O[1],w=n.data.get(s.dataId).values,j=0,S=0;S<d;S++)for(var N=S*u[0],I=0;I<m;I++)for(var C=I*x,T=Math.floor(C),E=Math.min(Math.ceil(C),f-1),A=N+T*u[1],R=N+E*u[1],F=C-T,D=1-F,_=0;_<v;_++)for(var M=_*k,z=Math.floor(M),L=Math.min(Math.ceil(M),p-1),P=M-z,B=1-P,W=A+z*u[2],U=A+L*u[2],V=R+z*u[2],H=R+L*u[2],G=D*B,q=D*P,K=F*B,X=F*P,Y=0;Y<h;Y++){var $=w[j++];g[W+Y]+=$*G,g[U+Y]+=$*q,g[V+Y]+=$*K,g[H+Y]+=$*X}return n.makeTensorInfo([d,p,f,h],"float32",g)}};var Mm={kernelName:i.sc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,s=r.alignCorners,c=r.halfPixelCenters,u=r.size;Yd(a,"resizeNearestNeighbor");for(var l=i.wf.computeStrides(a.shape),d=Object(o.a)(u,2),f=d[0],p=d[1],h=Object(o.a)(a.shape,4),b=h[0],m=h[1],v=h[2],g=h[3],y=n.data.get(a.dataId).values,O=new Float32Array(b*f*p*g),x=[s&&f>1?m-1:m,s&&p>1?v-1:v],k=[s&&f>1?f-1:f,s&&p>1?p-1:p],w=x[0]/k[0],j=x[1]/k[1],S=0,N=0;N<b;N++)for(var I=N*l[0],C=0;C<f;C++){var T=c?w*(C+.5):w*C,E=Math.min(m-1,s?Math.round(T):Math.floor(T));c&&(E=Math.max(0,E));for(var A=I+E*l[1],R=0;R<p;R++){var F=c?j*(R+.5):j*R,D=Math.min(v-1,s?Math.round(F):Math.floor(F));c&&(D=Math.max(0,D));for(var _=A+D*l[2],M=0;M<g;M++){var z=y[_+M];O[S++]=z}}}return n.makeTensorInfo([b,f,p,g],a.dtype,O)}};var zm={kernelName:i.tc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,s=t.dy,c=r.alignCorners;Yd([s,a],"resizeNearestNeighborGrad");for(var u=i.wf.computeStrides(a.shape),l=i.wf.computeStrides(s.shape),d=Object(o.a)(a.shape,4),f=d[0],p=d[1],h=d[2],b=d[3],m=Object(o.a)(s.shape,3),v=m[1],g=m[2],y=new Float32Array(f*p*h*b),O=n.data.get(s.dataId).values,x=[c&&v>1?p-1:p,c&&g>1?h-1:h],k=[c&&v>1?v-1:v,c&&g>1?g-1:g],w=x[0]/k[0],j=x[1]/k[1],S=1/w,N=1/j,I=2*Math.ceil(S)+2,C=2*Math.ceil(N)+2,T=0;T<f;T++)for(var E=T*u[0],A=0;A<p;A++)for(var R=E+A*u[1],F=Math.floor(A*S),D=Math.floor(F-I/2),_=0;_<h;_++)for(var M=R+_*u[2],z=Math.floor(_*N),L=Math.floor(z-C/2),P=0;P<b;P++){for(var B=0,W=0;W<I;W++){var U=W+D;if(!(U<0||U>=v)){var V=E+U*l[1],H=U*w;if(A===Math.min(p-1,c?Math.round(H):Math.floor(H)))for(var G=0;G<C;G++){var q=G+L;if(!(q<0||q>=g)){var K=V+q*l[2],X=q*j;_===Math.min(h-1,c?Math.round(X):Math.floor(X))&&(B+=O[K+P])}}}}y[M+P]=B}return n.makeTensorInfo(a.shape,a.dtype,y)}};var Lm={kernelName:i.uc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.dims;Yd(a,"reverse");var s=a.shape.length,c=i.wf.parseAxisParam(o,a.shape);if(0===s)return nf({inputs:{x:a},backend:n});for(var u=new i.cd(a.shape,a.dtype),l=n.bufferSync(a),d=function(e){var t=u.indexToLoc(e),n=t.slice();c.forEach((function(e){return n[e]=a.shape[e]-1-n[e]})),u.set.apply(u,[l.get.apply(l,Object(Vn.a)(n))].concat(Object(Vn.a)(t)))},f=0;f<u.size;f++)d(f);return n.makeTensorInfo(u.shape,u.dtype,u.values)}},Pm={kernelName:i.vc,backendName:"cpu",kernelFunc:function(e){for(var t=e.inputs,n=e.attrs,r=e.backend,a=t.image,s=n.radians,c=n.fillValue,u=n.center,l=r,d=i.wf.getTypedArrayFromDType(a.dtype,i.wf.sizeFromShape(a.shape)),f=Object(o.a)(a.shape,4),p=f[0],h=f[1],b=f[2],m=f[3],v=i.ud.getImageCenter(u,h,b),g=Object(o.a)(v,2),y=g[0],O=g[1],x=Math.sin(s),k=Math.cos(s),w=l.data.get(a.dataId).values,j=0;j<p;j++)for(var S=j*b*h*m,N=0;N<h;N++)for(var I=N*(b*m),C=0;C<b;C++)for(var T=C*m,E=0;E<m;E++){var A=[p,N,C,E],R=A[2],F=A[1],D=(R-y)*k-(F-O)*x,_=(R-y)*x+(F-O)*k;D=Math.round(D+y),_=Math.round(_+O);var M=c;if("number"!==typeof c&&(M=3===E?255:c[E]),D>=0&&D<b&&_>=0&&_<h)M=w[S+_*(b*m)+D*m+E];d[S+I+T+E]=M}return{dataId:l.write(d,a.shape,a.dtype),shape:a.shape,dtype:a.dtype}}},Bm=Zd(i.wc,(function(e){var t=Math.floor(e);return e-t<.5?Math.floor(e):e-t>.5?Math.ceil(e):t%2===0?t:t+1})),Wm={kernelName:i.wc,backendName:"cpu",kernelFunc:Bm},Um=kp((function(e){return 1/Math.sqrt(e)})),Vm=Jd(i.xc,Um),Hm={kernelName:i.xc,backendName:"cpu",kernelFunc:Vm};function Gm(e,t,n,r,a,o,s,c,u,l){var d=[r/a,a],f=e.values,p=t.values;if(0===r)return Object(i.zd)(n,t.dtype);var h=Object(i.zd)(d,t.dtype);h.values.fill(u);for(var b=0;b<o;b++){for(var m=[],v=0,g=0;g<s;g++){var y=f[b*s+g];m.push(y),v+=y*c[g]}if(v<0||v>=r/a)throw new Error("Invalid indices: ".concat(m," does not index into ").concat(n));for(var O=0;O<a;O++)l?h.values[v*a+O]+=p[b*a+O]:h.values[v*a+O]=0===t.rank?p[0]:p[b*a+O]}return h}var qm={kernelName:i.yc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.indices,o=t.updates,s=r.shape,c=i.ud.calculateShapes(o,a,s),u=c.sliceRank,l=c.numUpdates,d=c.sliceSize,f=c.strides,p=c.outputSize,h=Gm(n.bufferSync(a),n.bufferSync(o),s,p,d,l,u,f,0,!0);return n.makeTensorInfo(s,h.dtype,h.values)}};var Km={kernelName:i.zc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.condition,a=t.t,o=t.e;Yd([r,a,o],"select");for(var s=r.shape.length,c=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,l=n.data.get(o.dataId).values,d=Object(i.vf)(a.dtype,o.dtype),f=i.wf.makeZerosTypedArray(i.wf.sizeFromShape(a.shape),d),p=0,h=0===s||s>1||1===a.shape.length?1:i.wf.sizeFromShape(a.shape.slice(1)),b=0;b<c.length;b++)for(var m=0;m<h;m++)1===c[b]?f[p++]=u[b]:f[p++]=l[b];return n.makeTensorInfo(a.shape,d,f)}},Xm=i.ud.SELU_SCALEALPHA,Ym=i.ud.SELU_SCALE,$m=Zd(i.Ac,(function(e){return e>=0?Ym*e:Xm*(Math.exp(e)-1)})),Qm={kernelName:i.Ac,backendName:"cpu",kernelFunc:$m},Zm=Zd(i.Cc,(function(e){return e<0?-1:e>0?1:0})),Jm={kernelName:i.Cc,backendName:"cpu",kernelFunc:Zm},ev=Zd(i.Dc,(function(e){return Math.sin(e)})),tv={kernelName:i.Dc,backendName:"cpu",kernelFunc:ev},nv=Zd(i.Ec,(function(e){return Math.sinh(e)})),rv={kernelName:i.Ec,backendName:"cpu",kernelFunc:nv},av=Math.log(1.1920928955078125e-7)+2,iv=Zd(i.Hc,(function(e){var t=e>-av,n=e<av,r=Math.exp(e);return n?r:t?e:Math.log(1+r)})),ov={kernelName:i.Hc,backendName:"cpu",kernelFunc:iv};var sv={kernelName:i.Ic,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.blockShape,s=r.paddings;Yd([a],"spaceToBatchND");var c=i.wf.sizeFromShape(o),u=[[0,0]];u.push.apply(u,Object(Vn.a)(s));for(var l=1+o.length;l<a.shape.length;++l)u.push([0,0]);var d=jm.kernelFunc({inputs:{x:a},backend:n,attrs:{paddings:u,constantValue:0}}),f=i.ud.getReshaped(d.shape,o,c,!1),p=i.ud.getPermuted(f.length,o.length,!1),h=i.ud.getReshapedPermuted(d.shape,o,c,!1),b=Af({inputs:{x:d},backend:n,attrs:{shape:f}}),m=Hf({inputs:{x:b},backend:n,attrs:{perm:p}}),v=Af({inputs:{x:m},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(m),v}};function cv(e,t,n,r,a,o,s){var c=t[0],u=o[0],l=new Array(u),d=new Array(c),f=t[1];if(0===u){if(0!==c)throw new Error("Received SparseTensor with denseShape[0] = 0 but\n         indices.shape[0] = ".concat(c));return[i.wf.getArrayFromDType(n,0),[0,f],i.wf.getArrayFromDType(a,0),l,d]}for(var p=!0,h=0,b=new Array(u).fill(0),m=0;m<c;++m){var v=e[m*f];if(v<0)throw new Error("indices(".concat(m,", 0) is invalid: ").concat(v," < 0"));if(v>=u)throw new Error("indices(".concat(m,", 0) is invalid: ").concat(v," >= 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Error("Input indices should be a matrix but received shape\n        ".concat(r.shape));if(1!==a.shape.length)throw new Error("Input shape should be a vector but received shape\n        ".concat(a.shape));if(1!==i.shape.length)throw new Error("Target shape should be a vector but received shape ".concat(i.shape));var s=Array.from(n.data.get(a.dataId).values),c=n.data.get(r.dataId).values,u=Array.from(n.data.get(i.dataId).values),l=lv(c,r.shape,r.dtype,s,u),d=Object(o.a)(l,3),f=d[0],p=d[1],h=d[2];return[n.makeTensorInfo(p,r.dtype,f),n.makeTensorInfo([h.length],i.dtype,new Int32Array(h))]}};function fv(e,t,n,r,a){var o=arguments.length>5&&void 0!==arguments[5]&&arguments[5],s=arguments.length>6&&void 0!==arguments[6]?arguments[6]:0,c=r.length;if(c!==a.length)throw new Error("segmentIds and indices should have same size.");var u=[t[0],e.length/t[0]],l=u[1],d=c>0?a[c-1]+1:0,f=d;if(f<0)throw new Error("segment ids must be >= 0");var p=t.slice();p[0]=f;var h=p.reduce((function(e,t){return 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n.makeTensorInfo(p,r.dtype,f)}};var bv={kernelName:i.Nc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.sparseIndices,o=t.sparseValues,s=t.defaultValue,c=r.outputShape,u=i.ud.calculateShapes(o,a,c),l=u.sliceRank,d=u.numUpdates,f=u.sliceSize,p=u.strides,h=u.outputSize,b=Gm(n.bufferSync(a),n.bufferSync(o),c,h,f,d,l,p,n.data.get(s.dataId).values[0],!1);return n.makeTensorInfo(c,b.dtype,b.values)}};var mv={kernelName:i.Oc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.numOrSizeSplits,s=r.axis,c=i.wf.parseAxisParam(s,a.shape)[0],u=i.ud.prepareSplitSize(a,o,c),l=new Array(a.shape.length).fill(0),d=a.shape.slice();return u.map((function(e){var t=Object(Vn.a)(d);t[c]=e;var r=mp({inputs:{x:a},backend:n,attrs:{begin:l,size:t}});return l[c]+=e,r}))}},vv=Zd(i.Pc,(function(e){return Math.sqrt(e)})),gv={kernelName:i.Pc,backendName:"cpu",kernelFunc:vv},yv={kernelName:i.Qc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.x,a=n;Yd(r,"square");for(var i=a.data.get(r.dataId).values,o=new Float32Array(i.length),s=0;s<i.length;++s){var c=i[s];o[s]=c*c}return{dataId:a.write(o,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},Ov=sf((function(e,t){var n=e-t;return n*n})),xv=Sf(i.Rc,Ov),kv={kernelName:i.Rc,backendName:"cpu",kernelFunc:xv},wv=Zd(i.Sc,(function(e,t){var n=t;return isNaN(e)?NaN:e>0?1:n.alpha})),jv={kernelName:i.Sc,backendName:"cpu",kernelFunc:wv};function Sv(e,t,n,r){for(var a=Object(i.zd)(e,t.dtype),o=0;o<a.size;o++){for(var s=a.indexToLoc(o),c=new Array(s.length),u=0;u<c.length;u++)c[u]=s[u]*n[u]+r[u];a.set.apply(a,[t.get.apply(t,c)].concat(Object(Vn.a)(s)))}return a}var Nv={kernelName:i.Tc,backendName:"cpu",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.begin,s=r.end,c=r.strides,u=r.beginMask,l=r.endMask,d=r.ellipsisMask,f=r.newAxisMask,p=r.shrinkAxisMask;Yd(a,"stridedSlice");var h,b=i.af.sliceInfo(a.shape,o,s,c,u,l,d,f,p),m=b.nonStrided,v=b.$begin,g=b.$strides,y=b.size,O=b.newShape,x=b.outShape,k=Af({inputs:{x:a},backend:n,attrs:{shape:O}});if(m){var w=mp({inputs:{x:k},backend:n,attrs:{begin:v,size:y}});h=Af({inputs:{x:w},backend:n,attrs:{shape:x}}),n.disposeIntermediateTensorInfo(w)}else if(x.some((function(e){return 0===e})))h=n.makeTensorInfo(x,a.dtype,[]);else{var j=Sv(x,n.bufferSync(k),g,v);h=n.makeTensorInfo(j.shape,j.dtype,j.values)}var S=Af({inputs:{x:h},backend:n,attrs:{shape:x}});return n.disposeIntermediateTensorInfo(k),n.disposeIntermediateTensorInfo(h),S}},Iv=function(){function e(t,n,r,a,o,s){Object(Yr.a)(this,e),this.separator=i.wf.encodeString(t),this.nGramWidths=n,this.leftPad=i.wf.encodeString(r),this.rightPad=i.wf.encodeString(a),this.padWidth=o,this.preserveShort=s}return Object($r.a)(e,[{key:"getPadWidth",value:function(e){return Math.min(this.padWidth<0?e-1:this.padWidth,e-1)}},{key:"getNumNGrams",value:function(e,t){var n=this.getPadWidth(t);return Math.max(0,e+2*n-t+1)}},{key:"createNGrams",value:function(e,t,n,r,a,i){for(var o=this,s=function(s){var c=o.getPadWidth(i),u=Math.max(0,c-s),l=Math.max(0,c-(a-(s+1))),d=i-(u+l),f=t+(u>0?0:s-c),p=0;p+=u*o.leftPad.length;for(var h=0;h<d;++h)p+=e[f+h].length;p+=l*o.rightPad.length,p+=(u+l+d-1)*o.separator.length,n[r+s]=new Uint8Array(p);for(var b=n[r+s],m=0,v=function(e){return e.forEach((function(e){return b[m++]=e}))},g=0;g<u;++g)v(o.leftPad),v(o.separator);for(var y=0;y<d-1;++y)v(e[f+y]),v(o.separator);if(d>0){v(e[f+d-1]);for(var O=0;O<l;++O)v(o.separator),v(o.rightPad)}else{for(var x=0;x<l-1;++x)v(o.rightPad),v(o.separator);v(o.rightPad)}},c=0;c<a;++c)s(c)}},{key:"compute",value:function(e,t){var n=this,r=e.length,a=t.length;if(a>0){var o=t[0];if(0!==o)throw new Error("First split value must be 0, got ".concat(o));for(var s=1;s<a;++s){var c=t[s]>=o;if(!(c=c&&t[s]<=r))throw new Error("Invalid split value ".concat(t[s],", must be in [").concat(o,", ").concat(r,"]"));o=t[s]}if(o!==r)throw new Error("Last split value must be data size. 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u.bindBuffer(u.PIXEL_PACK_BUFFER,t),u.getBufferSubData(u.PIXEL_PACK_BUFFER,0,l),u.bindBuffer(u.PIXEL_PACK_BUFFER,null),l}var cy=function(){function e(t){Object(Yr.a)(this,e),this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];var n=Object(i.Ud)().getNumber("WEBGL_VERSION");null!=t?(this.gl=t,function(e,t){og[e]=t}(n,t)):this.gl=cg(n);var r="WEBGL_color_buffer_float",a="EXT_color_buffer_half_float";if(1===Object(i.Ud)().getNumber("WEBGL_VERSION")){var o="OES_texture_half_float";if(this.textureFloatExtension=bg(this.gl,"OES_texture_float"),_g(this.gl,o))this.textureHalfFloatExtension=bg(this.gl,o);else if(Object(i.Ud)().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(r),_g(this.gl,a))this.colorBufferHalfFloatExtension=bg(this.gl,a);else if(Object(i.Ud)().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(r="EXT_color_buffer_float",_g(this.gl,r))this.colorBufferFloatExtension=this.gl.getExtension(r);else{if(!_g(this.gl,a))throw new Error("GL context does not support color renderable floats");this.colorBufferHalfFloatExtension=this.gl.getExtension(a)}this.vertexBuffer=Jg(this.gl),this.indexBuffer=ey(this.gl),this.framebuffer=function(e){return Cg(e,(function(){return e.createFramebuffer()}),"Unable to create WebGLFramebuffer.")}(this.gl),this.textureConfig=fg(this.gl,this.textureHalfFloatExtension)}return Object($r.a)(e,[{key:"debug",get:function(){return Object(i.Ud)().getBool("DEBUG")}},{key:"dispose",value:function(){var e=this;if(!this.disposed){null!=this.program&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),null!=this.outputTexture&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");var t=this.gl;pg(t,(function(){return t.finish()})),pg(t,(function(){return t.bindFramebuffer(t.FRAMEBUFFER,null)})),pg(t,(function(){return t.deleteFramebuffer(e.framebuffer)})),pg(t,(function(){return t.bindBuffer(t.ARRAY_BUFFER,null)})),pg(t,(function(){return t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null)})),pg(t,(function(){return t.deleteBuffer(e.indexBuffer)})),this.disposed=!0}}},{key:"createFloat32MatrixTexture",value:function(e,t){return this.throwIfDisposed(),function(e,t,n,r){var a=ug(t,n),i=Object(o.a)(a,2);return ty(e,i[0],i[1],ny(r),r.textureFormatFloat,e.FLOAT)}(this.gl,e,t,this.textureConfig)}},{key:"createFloat16MatrixTexture",value:function(e,t){return this.throwIfDisposed(),function(e,t,n,r){var a=ug(t,n),i=Object(o.a)(a,2);return ty(e,i[0],i[1],ry(r),r.textureFormatFloat,r.textureTypeHalfFloat)}(this.gl,e,t,this.textureConfig)}},{key:"createUnsignedBytesMatrixTexture",value:function(e,t){return this.throwIfDisposed(),function(e,t,n,r){var a=ug(t,n),i=Object(o.a)(a,2);return ty(e,i[0],i[1],ay(r),e.RGBA,e.UNSIGNED_BYTE)}(this.gl,e,t,this.textureConfig)}},{key:"uploadPixelDataToTexture",value:function(e,t){this.throwIfDisposed(),function(e,t,n){pg(e,(function(){return e.bindTexture(e.TEXTURE_2D,t)})),n.data instanceof Uint8Array?pg(e,(function(){return e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)})):pg(e,(function(){return e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)})),pg(e,(function(){return e.bindTexture(e.TEXTURE_2D,null)}))}(this.gl,e,t)}},{key:"uploadDenseMatrixToTexture",value:function(e,t,n,r){this.throwIfDisposed(),function(e,t,n,r,a,i){var o,s,c;pg(e,(function(){return e.bindTexture(e.TEXTURE_2D,t)})),a instanceof Uint8Array?(o=new Uint8Array(n*r*4),s=e.UNSIGNED_BYTE,c=e.RGBA):(o=new Float32Array(n*r*4),s=e.FLOAT,c=i.internalFormatPackedFloat),o.set(a),pg(e,(function(){return e.texImage2D(e.TEXTURE_2D,0,c,n,r,0,e.RGBA,s,o)})),pg(e,(function(){return e.bindTexture(e.TEXTURE_2D,null)}))}(this.gl,e,t,n,r,this.textureConfig)}},{key:"createFloat16PackedMatrixTexture",value:function(e,t){return this.throwIfDisposed(),function(e,t,n,r){var a=dg(t,n),i=Object(o.a)(a,2);return ty(e,i[0],i[1],oy(r),e.RGBA,r.textureTypeHalfFloat)}(this.gl,e,t,this.textureConfig)}},{key:"createPackedMatrixTexture",value:function(e,t){return this.throwIfDisposed(),function(e,t,n,r){var a=dg(t,n),i=Object(o.a)(a,2);return ty(e,i[0],i[1],iy(r),e.RGBA,e.FLOAT)}(this.gl,e,t,this.textureConfig)}},{key:"deleteMatrixTexture",value:function(e){var t=this;this.throwIfDisposed(),this.outputTexture===e&&(Ng(this.gl,this.framebuffer),this.outputTexture=null),pg(this.gl,(function(){return t.gl.deleteTexture(e)}))}},{key:"downloadByteEncodedFloatMatrixFromOutputTexture",value:function(e,t,n){var r=this;return this.downloadMatrixDriver(e,(function(){return function(e,t,n,r){var a=ug(t,n),i=Object(o.a)(a,2),s=i[0],c=i[1],u=new Uint8Array(t*n*4);return pg(e,(function(){return e.readPixels(0,0,s,c,r.downloadTextureFormat,e.UNSIGNED_BYTE,u)})),new Float32Array(u.buffer)}(r.gl,t,n,r.textureConfig)}))}},{key:"downloadPackedMatrixFromBuffer",value:function(e,t,n,r,a,i){return sy(this.gl,e,0,0,0,a,i,this.textureConfig)}},{key:"downloadFloat32MatrixFromBuffer",value:function(e,t){return function(e,t,n){var r=e,a=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,t),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,a),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),a}(this.gl,e,t)}},{key:"createBufferFromTexture",value:function(e,t,n){this.bindTextureToFrameBuffer(e);var r=function(e,t,n,r){var a=e.createBuffer();pg(e,(function(){return e.bindBuffer(e.PIXEL_PACK_BUFFER,a)}));var i=16*t*n;return pg(e,(function(){return e.bufferData(e.PIXEL_PACK_BUFFER,i,e.STREAM_READ)})),pg(e,(function(){return e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)})),pg(e,(function(){return e.bindBuffer(e.PIXEL_PACK_BUFFER,null)})),a}(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r}},{key:"createAndWaitForFence",value:function(){var e=this.createFence(this.gl);return this.pollFence(e)}},{key:"createFence",value:function(e){var t,n,r=this;if(Object(i.Ud)().getBool("WEBGL_FENCE_API_ENABLED")){var a=e,o=a.fenceSync(a.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=function(){var e=a.clientWaitSync(o,0,0);return e===a.ALREADY_SIGNALED||e===a.CONDITION_SATISFIED},t=o}else Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=function(){return r.isQueryAvailable(t,Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}):n=function(){return!0};return{query:t,isFencePassed:n}}},{key:"downloadMatrixFromPackedTexture",value:function(e,t,n){var r=this;return this.downloadMatrixDriver(e,(function(){return function(e,t,n){var r=new Float32Array(t*n*4);return pg(e,(function(){return e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,r)})),r}(r.gl,t,n)}))}},{key:"createProgram",value:function(e){var t=this;this.throwIfDisposed();var n=this.gl,r=mg(n,e);null==this.vertexShader&&(this.vertexShader=Zg(n));var a=function(e){return Cg(e,(function(){return e.createProgram()}),"Unable to create WebGLProgram.")}(n);return pg(n,(function(){return n.attachShader(a,t.vertexShader)})),pg(n,(function(){return n.attachShader(a,r)})),function(e,t){if(pg(e,(function(){return e.linkProgram(t)})),!1===e.getProgramParameter(t,e.LINK_STATUS))throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}(n,a),this.debug&&Og(n,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=function(e,t,n){return pg(e,(function(){return e.bindBuffer(e.ARRAY_BUFFER,n)})),xg(e,t,"clipSpacePos",n,3,20,0)&&xg(e,t,"uv",n,2,20,12)}(n,this.program,this.vertexBuffer)),a}},{key:"deleteProgram",value:function(e){var t=this;this.throwIfDisposed(),e===this.program&&(this.program=null),null!=e&&pg(this.gl,(function(){return t.gl.deleteProgram(e)}))}},{key:"setProgram",value:function(e){var t=this;this.throwIfDisposed(),this.program=e,null!=this.program&&this.debug&&Og(this.gl,this.program),pg(this.gl,(function(){return t.gl.useProgram(e)}))}},{key:"getUniformLocation",value:function(e,t){var n=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];return this.throwIfDisposed(),n?kg(this.gl,e,t):wg(this.gl,e,t)}},{key:"getAttributeLocation",value:function(e,t){var n=this;return this.throwIfDisposed(),pg(this.gl,(function(){return n.gl.getAttribLocation(e,t)}))}},{key:"getUniformLocationNoThrow",value:function(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}},{key:"setInputMatrixTexture",value:function(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),jg(this.gl,e,t,n)}},{key:"setOutputMatrixTexture",value:function(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}},{key:"setOutputPackedMatrixTexture",value:function(e,t,n){this.throwIfDisposed();var r=dg(t,n),a=Object(o.a)(r,2),i=a[0],s=a[1];this.setOutputMatrixTextureDriver(e,i,s)}},{key:"setOutputMatrixWriteRegion",value:function(e,t,n,r){this.setOutputMatrixWriteRegionDriver(n,e,r,t)}},{key:"setOutputPackedMatrixWriteRegion",value:function(e,t,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}},{key:"debugValidate",value:function(){null!=this.program&&Og(this.gl,this.program),Ig(this.gl)}},{key:"executeProgram",value:function(){this.throwIfDisposed(),this.throwIfNoProgram();var e=this.gl;this.debug&&this.debugValidate(),pg(e,(function(){return e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0)}))}},{key:"blockUntilAllProgramsCompleted",value:function(){var e=this;this.throwIfDisposed(),pg(this.gl,(function(){return e.gl.finish()}))}},{key:"getQueryTimerExtension",value:function(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=bg(this.gl,2===Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}},{key:"getQueryTimerExtensionWebGL2",value:function(){return this.getQueryTimerExtension()}},{key:"getQueryTimerExtensionWebGL1",value:function(){return this.getQueryTimerExtension()}},{key:"beginQuery",value:function(){if(2===Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var e=this.gl,t=this.getQueryTimerExtensionWebGL2(),n=e.createQuery();return e.beginQuery(t.TIME_ELAPSED_EXT,n),n}var r=this.getQueryTimerExtensionWebGL1(),a=r.createQueryEXT();return r.beginQueryEXT(r.TIME_ELAPSED_EXT,a),a}},{key:"endQuery",value:function(){if(2!==Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}else{var t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT)}}},{key:"waitForQueryAndGetTime",value:function(){var e=Object(go.a)(vo.a.mark((function e(t){var n=this;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:return e.next=2,i.wf.repeatedTry((function(){return n.disposed||n.isQueryAvailable(t,Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}));case 2:return e.abrupt("return",this.getQueryTime(t,Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")));case 3:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}()},{key:"getQueryTime",value:function(e,t){if(0===t)return null;if(2===t){var n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}var r=this.getQueryTimerExtensionWebGL1();return r.getQueryObjectEXT(e,r.QUERY_RESULT_EXT)/1e6}},{key:"isQueryAvailable",value:function(e,t){if(0===t)return!0;if(2===t){var n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),a&&!this.disjoint}var i=this.getQueryTimerExtensionWebGL1(),o=i.getQueryObjectEXT(e,i.QUERY_RESULT_AVAILABLE_EXT);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(i.GPU_DISJOINT_EXT)),o&&!this.disjoint}},{key:"pollFence",value:function(e){var t=this;return new Promise((function(n){t.addItemToPoll((function(){return e.isFencePassed()}),(function(){return n()}))}))}},{key:"pollItems",value:function(){for(var e=function(e){for(var t=0;t<e.length;++t){if(!e[t]())break}return t-1}(this.itemsToPoll.map((function(e){return e.isDoneFn}))),t=0;t<=e;++t){(0,this.itemsToPoll[t].resolveFn)()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}},{key:"addItemToPoll",value:function(e,t){var n=this;this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1||i.wf.repeatedTry((function(){return n.pollItems(),0===n.itemsToPoll.length}))}},{key:"bindTextureToFrameBuffer",value:function(e){this.throwIfDisposed(),Sg(this.gl,e,this.framebuffer),this.debug&&Ig(this.gl)}},{key:"unbindTextureToFrameBuffer",value:function(){null!=this.outputTexture?(Sg(this.gl,this.outputTexture,this.framebuffer),this.debug&&Ig(this.gl)):Ng(this.gl,this.framebuffer)}},{key:"downloadMatrixDriver",value:function(e,t){this.bindTextureToFrameBuffer(e);var n=t();return this.unbindTextureToFrameBuffer(),n}},{key:"setOutputMatrixTextureDriver",value:function(e,t,n){this.throwIfDisposed();var r=this.gl;Sg(r,e,this.framebuffer),this.debug&&Ig(r),this.outputTexture=e,pg(r,(function(){return r.viewport(0,0,t,n)})),pg(r,(function(){return r.scissor(0,0,t,n)}))}},{key:"setOutputMatrixWriteRegionDriver",value:function(e,t,n,r){var a=this;this.throwIfDisposed(),pg(this.gl,(function(){return a.gl.scissor(e,t,n,r)}))}},{key:"throwIfDisposed",value:function(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}},{key:"throwIfNoProgram",value:function(){if(null==this.program)throw new Error("No GPU program is currently set.")}}]),e}();var uy=i.ud.getBroadcastDims;function ly(e,t,n){var r=[];if(e.forEach((function(e){var t=i.wf.sizeFromShape(e.shapeInfo.logicalShape);if(e.shapeInfo.isUniform?r.push("uniform float ".concat(e.name).concat(t>1?"[".concat(t,"]"):"",";")):(r.push("uniform sampler2D ".concat(e.name,";")),r.push("uniform int offset".concat(e.name,";"))),n.enableShapeUniforms){switch(Ty(n.packedInputs,e.shapeInfo.logicalShape,e.shapeInfo.texShape).uniformShape.length){case 1:r.push("uniform int ".concat(e.name,"Shape;"));break;case 2:r.push("uniform ivec2 ".concat(e.name,"Shape;"));break;case 3:r.push("uniform ivec3 ".concat(e.name,"Shape;"));break;case 4:r.push("uniform ivec4 ".concat(e.name,"Shape;"))}r.push("uniform ivec2 ".concat(e.name,"TexShape;"))}})),n.enableShapeUniforms){switch(t.logicalShape.length){case 1:r.push("uniform int outShape;");break;case 2:r.push("uniform ivec2 outShape;"),r.push("uniform int outShapeStrides;");break;case 3:r.push("uniform ivec3 outShape;"),r.push("uniform ivec2 outShapeStrides;");break;case 4:r.push("uniform ivec4 outShape;"),r.push("uniform ivec3 outShapeStrides;")}r.push("uniform ivec2 outTexShape;")}n.customUniforms&&n.customUniforms.forEach((function(e){r.push("uniform ".concat(e.type," ").concat(e.name).concat(e.arrayIndex?"[".concat(e.arrayIndex,"]"):"",";"))}));var a,o,s=r.join("\n"),c=e.map((function(e){return function(e,t){var n=arguments.length>2&&void 0!==arguments[2]&&arguments[2],r=arguments.length>3?arguments[3]:void 0,a="";a+=n?fy(e,r):dy(e,r);var i=e.shapeInfo.logicalShape,o=t.logicalShape;i.length<=o.length&&(a+=n?Ny(e,t):Iy(e,t));return a}(e,t,n.packedInputs,n.enableShapeUniforms)})).join("\n"),u=t.texShape,l=Wg(),d=function(e){return"\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return ".concat(e.texture2D,"(textureSampler, uv).r;\n    }\n  ")}(l),f=function(e){return"".concat(e.version,"\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    ").concat(e.varyingFs," vec2 resultUV;\n    ").concat(e.defineOutput,"\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    uniform float NAN;\n    ").concat(e.defineSpecialNaN,"\n    ").concat(e.defineSpecialInf,"\n    ").concat(e.defineRound,"\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    int idiv(int a, int b, float sign) {\n      int res = a / b;\n      int mod = imod(a, b);\n      if (sign < 0. && mod != 0) {\n        res -= 1;\n      }\n      return res;\n    }\n\n    //Based on the work of Dave Hoskins\n    //https://www.shadertoy.com/view/4djSRW\n    #define HASHSCALE1 443.8975\n    float random(float seed){\n      vec2 p = resultUV * seed;\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n      p3 += dot(p3, p3.yzx + 19.19);\n      return fract((p3.x + p3.y) * p3.z);\n    }\n\n    ").concat(py,"\n    ").concat(hy,"\n    ").concat(by,"\n  ")}(l);return t.isPacked?(a=function(e,t,n){switch(e.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return function(e,t,n){var r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(1===r[0])return n?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));\n      }\n    ":"\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * ".concat(r[1],".0);\n      }\n    ");if(1===r[1])return n?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));\n      }\n    ":"\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * ".concat(r[0],".0);\n      }\n    ");if(n)return"\n    int getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);\n    }\n  ";return"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(".concat(r[0],", ").concat(r[1],"));\n      return 2 * (resTexRC.x * ").concat(r[1]," + resTexRC.y);\n    }\n  ")}(0,t,n);case 2:return function(e,t,n){var r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(i.wf.arraysEqual(e,t))return n?"\n      ivec2 getOutputCoords() {\n        ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n        return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));\n      }\n    ":"\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2(".concat(r[0],", ").concat(r[1],"));\n      }\n    ");var a=Math.ceil(e[1]/2);if(n)return"\n    ivec2 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec2(r, c);\n    }\n  ";return"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(".concat(r[0],", ").concat(r[1],"));\n\n      int index = resTexRC.x * ").concat(r[1]," + resTexRC.y;\n      int r = 2 * (index / ").concat(a,");\n      int c = imod(index, ").concat(a,") * 2;\n\n      return ivec2(r, c);\n    }\n  ")}(e,t,n);case 3:return function(e,t,n){if(n)return"\n    ivec3 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));\n      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n      int b = index / texelsInBatch;\n      index -= b * texelsInBatch;\n\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec3(b, r, c);\n    }\n  ";var r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[2]/2),i=a*Math.ceil(e[1]/2);return"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(".concat(r[0],", ").concat(r[1],"));\n      int index = resTexRC.x * ").concat(r[1]," + resTexRC.y;\n\n      int b = index / ").concat(i,";\n      index -= b * ").concat(i,";\n\n      int r = 2 * (index / ").concat(a,");\n      int c = imod(index, ").concat(a,") * 2;\n\n      return ivec3(b, r, c);\n    }\n  ")}(e,t,n);default:return function(e,t,n){if(n)return"\n    ivec4 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n      int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));\n      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));\n      int texelsInBatchN = texelsInBatch * outShape[1];\n\n      int b2 = index / texelsInBatchN;\n      index -= b2 * texelsInBatchN;\n\n      int b = index / texelsInBatch;\n      index -= b * texelsInBatch;\n\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec4(b2, b, r, c);\n    }\n  ";for(var r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[e.length-1]/2),i=a*Math.ceil(e[e.length-2]/2),o=i,s="",c="b, r, c",u=2;u<e.length-1;u++)o*=e[e.length-u-1],s="\n      int b".concat(u," = index / ").concat(o,";\n      index -= b").concat(u," * ").concat(o,";\n    ")+s,c="b".concat(u,", ")+c;return"\n    ivec".concat(e.length," getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(").concat(r[0],", ").concat(r[1],"));\n      int index = resTexRC.x * ").concat(r[1]," + resTexRC.y;\n\n      ").concat(s,"\n\n      int b = index / ").concat(i,";\n      index -= b * ").concat(i,";\n\n      int r = 2 * (index / ").concat(a,");\n      int c = imod(index, ").concat(a,") * 2;\n\n      return ivec").concat(e.length,"(").concat(c,");\n    }\n  ")}(e,t,n)}}(t.logicalShape,u,n.enableShapeUniforms),o=function(e){return"\n    void setOutput(vec4 val) {\n      ".concat(e.output," = val;\n    }\n  ")}(l)):(a=function(e,t,n){switch(e.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return function(e,t,n){if(1===t[0])return n?"\n      int getOutputCoords() {\n        return int(resultUV.x * float(outTexShape[1]));\n      }\n    ":"\n      int getOutputCoords() {\n        return int(resultUV.x * ".concat(t[1],".0);\n      }\n    ");if(1===t[1])return n?"\n      int getOutputCoords() {\n        return int(resultUV.y * float(outTexShape[0]));\n      }\n    ":"\n      int getOutputCoords() {\n        return int(resultUV.y * ".concat(t[0],".0);\n      }\n    ");if(n)return"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(outTexShape[0], outTexShape[1]));\n      return resTexRC.x * outTexShape[1] + resTexRC.y;\n    }\n  ";return"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(".concat(t[0],", ").concat(t[1],"));\n      return resTexRC.x * ").concat(t[1]," + resTexRC.y;\n    }\n  ")}(0,t,n);case 2:return function(e,t,n){if(i.wf.arraysEqual(e,t))return n?"\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));\n      }\n    ":"\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2(".concat(t[0],", ").concat(t[1],"));\n      }\n    ");if(1===e[1])return n?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(outTexShape[0], outTexShape[1]));\n        int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ":"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(".concat(t[0],", ").concat(t[1],"));\n        int index = resTexRC.x * ").concat(t[1]," + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ");if(1===e[0])return n?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(outTexShape[0], outTexShape[1]));\n        int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ":"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(".concat(t[0],", ").concat(t[1],"));\n        int index = resTexRC.x * ").concat(t[1]," + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ");if(n)return"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(outTexShape[0], outTexShape[1]));\n      int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n      int r = index / outShape[1];\n      int c = index - r * outShape[1];\n      return ivec2(r, c);\n    }\n  ";return"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(".concat(t[0],", ").concat(t[1],"));\n      int index = resTexRC.x * ").concat(t[1]," + resTexRC.y;\n      int r = index / ").concat(e[1],";\n      int c = index - r * ").concat(e[1],";\n      return ivec2(r, c);\n    }\n  ")}(e,t,n);case 3:return function(e,t,n){if(n){var r=Vg(["r","c","d"],e);return"\n  ivec3 getOutputCoords() {\n    ivec2 resTexRC = ivec2(resultUV.yx *\n                           vec2(outTexShape[0], outTexShape[1]));\n    int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n    ".concat(r,"\n    return ivec3(r, c, d);\n  }\n")}var a=Ug(["r","c","d"],e);return"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(".concat(t[0],", ").concat(t[1],"));\n      int index = resTexRC.x * ").concat(t[1]," + resTexRC.y;\n      ").concat(a,"\n      return ivec3(r, c, d);\n    }\n  ")}(e,t,n);case 4:return function(e,t,n){if(n){var r=Vg(["r","c","d","d2"],e);return"\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(outTexShape[0], outTexShape[1]));\n      int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n      ".concat(r,"\n      return ivec4(r, c, d, d2);\n    }\n  ")}var a=Ug(["r","c","d","d2"],e);return"\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(".concat(t[0],", ").concat(t[1],"));\n      int index = resTexRC.x * ").concat(t[1]," + resTexRC.y;\n      ").concat(a,"\n      return ivec4(r, c, d, d2);\n    }\n  ")}(e,t,n);case 5:return function(e,t){var n=Ug(["r","c","d","d2","d3"],e);return"\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2(".concat(t[0],",\n                             ").concat(t[1],"));\n\n      int index = resTexRC.x * ").concat(t[1]," + resTexRC.y;\n\n      ").concat(n,"\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  ")}(e,t);case 6:return function(e,t){var n=Ug(["r","c","d","d2","d3","d4"],e);return"\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(".concat(t[0],", ").concat(t[1],"));\n      int index = resTexRC.x * ").concat(t[1]," + resTexRC.y;\n\n      ").concat(n,"\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  ")}(e,t);default:throw new Error("".concat(e.length,"-D output sampling is not yet supported"))}}(t.logicalShape,u,n.enableShapeUniforms),o=function(e){return"\n    void setOutput(float val) {\n      ".concat(e.output," = vec4(val, 0, 0, 0);\n    }\n  ")}(l)),n.packedInputs&&(f+=my),[f,d,o,s,a,c,n.userCode].join("\n")}function dy(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=e.shapeInfo.logicalShape;switch(n.length){case 0:return gy(e,t);case 1:return yy(e,t);case 2:return Oy(e,t);case 3:return xy(e,t);case 4:return ky(e,t);case 5:return wy(e);case 6:return jy(e);default:throw new Error("".concat(n.length,"-D input sampling")+" is not yet supported")}}function fy(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return function(e){var t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=Wg();return"\n    vec4 ".concat(n,"() {\n      return ").concat(r.texture2D,"(").concat(t,", halfCR);\n    }\n  ")}(e);case 1:return function(e,t){var n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,i=Wg();if(t)return"\n    vec4 ".concat(r,"(int index) {\n      ivec2 packedTexShape = ivec2(ceil(float(").concat(n,"TexShape[0]) / 2.0), ceil(float(").concat(n,"TexShape[1]) / 2.0));\n      vec2 uv = packedUVfrom1D(\n        packedTexShape[0], packedTexShape[1], index);\n      return ").concat(i.texture2D,"(").concat(n,", uv);\n    }\n  ");var o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];return"\n    vec4 ".concat(r,"(int index) {\n      vec2 uv = packedUVfrom1D(\n        ").concat(o[0],", ").concat(o[1],", index);\n      return ").concat(i.texture2D,"(").concat(n,", uv);\n    }\n  ")}(e,t);case 2:return function(e,t){var n=e.shapeInfo.logicalShape,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),o=e.shapeInfo.texShape,s=o[0],c=o[1],u=Wg();if(null!=o&&i.wf.arraysEqual(n,o))return t?"\n      vec4 ".concat(a,"(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(").concat(r,"TexShape[1], ").concat(r,"TexShape[0]);\n\n        return ").concat(u.texture2D,"(").concat(r,", uv);\n      }\n    "):"\n      vec4 ".concat(a,"(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(").concat(c,".0, ").concat(s,".0);\n\n        return ").concat(u.texture2D,"(").concat(r,", uv);\n      }\n    ");if(t)return"\n    vec4 ".concat(a,"(int row, int col) {\n      ivec2 packedTexShape = ivec2(ceil(float(").concat(r,"TexShape[0]) / 2.0), ceil(float(").concat(r,"TexShape[1]) / 2.0));\n      int valuesPerRow = int(ceil(float(").concat(r,"Shape[1]) / 2.0));\n      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);\n      return ").concat(u.texture2D,"(").concat(r,", uv);\n    }\n  ");var l=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],d=Math.ceil(n[1]/2);return"\n    vec4 ".concat(a,"(int row, int col) {\n      vec2 uv = packedUVfrom2D(").concat(d,", ").concat(l[0],", ").concat(l[1],", row, col);\n      return ").concat(u.texture2D,"(").concat(r,", uv);\n    }\n  ")}(e,t);case 3:return function(e,t){var n=e.shapeInfo.logicalShape,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),i=e.shapeInfo.texShape,o=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)];if(1===n[0]){var s=[1,2],c=Ey(e,n.slice(1)),u=["b","row","col"];return"\n        ".concat(fy(c,t),"\n        vec4 ").concat(a,"(int b, int row, int col) {\n          return ").concat(a,"(").concat(Ay(u,s),");\n        }\n      ")}var l=Wg();if(t)return"\n    vec4 ".concat(a,"(int b, int row, int col) {\n      ivec2 packedTexShape = ivec2(ceil(float(").concat(r,"TexShape[0]) / 2.0), ceil(float(").concat(r,"TexShape[1]) / 2.0));\n      int valuesPerRow = int(ceil(float(").concat(r,"Shape[2]) / 2.0));\n      int texelsInBatch = valuesPerRow * int(ceil(float(").concat(r,"Shape[1]) / 2.0));\n      vec2 uv = packedUVfrom3D(\n        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);\n      return ").concat(l.texture2D,"(").concat(r,", uv);\n    }\n  ");var d=o[0],f=o[1],p=Math.ceil(n[2]/2),h=p*Math.ceil(n[1]/2);return"\n    vec4 ".concat(a,"(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        ").concat(d,", ").concat(f,", ").concat(h,", ").concat(p,", b, row, col);\n      return ").concat(l.texture2D,"(").concat(r,", uv);\n    }\n  ")}(e,t);default:return function(e,t){var n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=Wg();if(t)return"\n    vec4 ".concat(r,"(int b2, int b, int row, int col) {\n      int valuesPerRow = int(ceil(float(").concat(n,"Shape[3]) / 2.0));\n      int texelsInBatch = valuesPerRow * int(ceil(float(").concat(n,"Shape[2]) / 2.0));\n      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);\n      texelsInBatch *= ").concat(n,"Shape[1];\n      index = b2 * texelsInBatch + index;\n      ivec2 packedTexShape = ivec2(ceil(float(").concat(n,"TexShape[0]) / 2.0), ceil(float(").concat(n,"TexShape[1]) / 2.0));\n      int texR = index / packedTexShape[1];\n      int texC = index - texR * packedTexShape[1];\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ").concat(a.texture2D,"(").concat(n,", uv);\n    }\n  ");for(var i=e.shapeInfo.logicalShape,o=i.length,s=e.shapeInfo.texShape,c=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],u=c[0],l=c[1],d=Math.ceil(i[o-1]/2),f=d*Math.ceil(i[o-2]/2),p="int b, int row, int col",h="b * ".concat(f," + (row / 2) * ").concat(d," + (col / 2)"),b=2;b<o-1;b++)p="int b".concat(b,", ")+p,f*=i[o-b-1],h="b".concat(b," * ").concat(f," + ")+h;return"\n    vec4 ".concat(r,"(").concat(p,") {\n      int index = ").concat(h,";\n      int texR = index / ").concat(l,";\n      int texC = index - texR * ").concat(l,";\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(").concat(l,", ").concat(u,");\n      return ").concat(a.texture2D,"(").concat(n,", uv);\n    }\n  ")}(e,t)}}var py="\nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",hy="\nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",by="\nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / 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u=Object(o.a)(e.shapeInfo.texShape,2),l=u[0],d=u[1];return"\n    float ".concat(r,"() {\n      vec2 uv = uvFromFlat(").concat(l,", ").concat(d,", ").concat(c,");\n      return sampleTexture(").concat(n,", uv);\n    }\n  ")}function yy(e,t){var n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return"\n      float ".concat(r,"(int index) {\n        ").concat(Sy(e),"\n      }\n    ");var a=e.shapeInfo.texShape,i=a[0],o=a[1];if(1===o&&1===i)return"\n      float ".concat(r,"(int index) {\n        return sampleTexture(").concat(n,", halfCR);\n      }\n    ");var s=vy(n);return 1===o?t?"\n      float ".concat(r,"(int index) {\n        vec2 uv = vec2(0.5, (float(index + ").concat(s,") + 0.5) / float(").concat(n,"TexShape[0]));\n        return sampleTexture(").concat(n,", uv);\n      }\n    "):"\n      float ".concat(r,"(int index) {\n        vec2 uv = vec2(0.5, (float(index + ").concat(s,") + 0.5) / ").concat(i,".0);\n        return sampleTexture(").concat(n,", 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sampleTexture(").concat(r,", uv);\n      }\n    "):"\n      float ".concat(a,"(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3(").concat(n[1]*n[2],", ").concat(n[2],", 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(").concat(m,".0, ").concat(b,".0);\n        return sampleTexture(").concat(r,", uv);\n      }\n    ");var O=vy(r);return t?"\n    float ".concat(a,"(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      ").concat(v,"\n      ").concat(g,"\n      ").concat(y,"\n      int index = row * stride0 + col * stride1 +\n          depth * stride2 + depth2;\n      vec2 uv = uvFromFlat(").concat(r,"TexShape[0], ").concat(r,"TexShape[1], index + ").concat(O,");\n      return sampleTexture(").concat(r,", uv);\n    }\n  "):"\n    float ".concat(a,"(int row, int col, int depth, int 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depth4 + ").concat(g,";\n      vec2 uv = uvFromFlat(").concat(m,", ").concat(v,", index);\n      return sampleTexture(").concat(n,", uv);\n    }\n  ")}function Sy(e){var t=e.name,n=i.wf.sizeFromShape(e.shapeInfo.logicalShape);return n<2?"return ".concat(t,";"):"\n    for (int i = 0; i < ".concat(n,"; i++) {\n      if (i == index) {\n        return ").concat(t,"[i];\n      }\n    }\n  ")}function Ny(e,t){var n,r=e.name,a=r.charAt(0).toUpperCase()+r.slice(1),o="get"+a+"AtOutCoords",s=e.shapeInfo.logicalShape.length,c=t.logicalShape.length,u=uy(e.shapeInfo.logicalShape,t.logicalShape),l=Cy(c),d=c-s,f=["x","y","z","w","u","v"];n=0===s?"":c<2&&u.length>=1?"coords = 0;":u.map((function(e){return"coords.".concat(f[e+d]," = 0;")})).join("\n");var p="";p=c<2&&s>0?"coords":e.shapeInfo.logicalShape.map((function(e,t){return"coords.".concat(f[t+d])})).join(", ");var h="return 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n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",o=t.texShape,s=e.shapeInfo.texShape,c=e.shapeInfo.logicalShape.length,u=t.logicalShape.length;if(!e.shapeInfo.isUniform&&c===u&&null==e.shapeInfo.flatOffset&&i.wf.arraysEqual(s,o))return"\n      float ".concat(a,"() {\n        return sampleTexture(").concat(n,", resultUV);\n      }\n    ");var l,d=Cy(u),f=uy(e.shapeInfo.logicalShape,t.logicalShape),p=u-c,h=["x","y","z","w","u","v"];l=0===c?"":u<2&&f.length>=1?"coords = 0;":f.map((function(e){return"coords.".concat(h[e+p]," = 0;")})).join("\n");var b="";return b=u<2&&c>0?"coords":e.shapeInfo.logicalShape.map((function(e,t){return"coords.".concat(h[t+p])})).join(", "),"\n    float ".concat(a,"() {\n      ").concat(d," coords = getOutputCoords();\n      ").concat(l,"\n      return get").concat(r,"(").concat(b,");\n    }\n  ")}function 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e.shapeInfo})),s={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},c=ly(a,s,t),u=e.createProgram(c),l=null,d=e.getUniformLocation(u,"NAN",!1);1===Object(i.Ud)().getNumber("WEBGL_VERSION")&&(l=e.getUniformLocation(u,"INFINITY",!1));for(var f,p,h,b=!1,m={},v={},g={},y=0;y<t.variableNames.length;y++){var O=t.variableNames[y];m[O]=e.getUniformLocation(u,O,b),m["offset".concat(O)]=e.getUniformLocation(u,"offset".concat(O),b),t.enableShapeUniforms&&(v["".concat(O,"Shape")]=e.getUniformLocation(u,"".concat(O,"Shape"),b),g["".concat(O,"TexShape")]=e.getUniformLocation(u,"".concat(O,"TexShape"),b))}t.enableShapeUniforms&&(f=e.getUniformLocation(u,"outShape",b),h=e.getUniformLocation(u,"outShapeStrides",b),p=e.getUniformLocation(u,"outTexShape",b));var x=[];return t.customUniforms&&t.customUniforms.forEach((function(t,n){x[n]=e.getUniformLocation(u,t.name,b)})),{program:t,source:c,webGLProgram:u,uniformLocations:m,customUniformLocations:x,inShapeInfos:o,outShapeInfo:s,infLoc:l,nanLoc:d,inShapesLocations:v,inTexShapesLocations:g,outShapeLocation:f,outShapeStridesLocation:h,outTexShapeLocation:p}}function Fy(e,t){if(e.length!==t.length)throw Error("Binary was compiled with ".concat(e.length," inputs, but ")+"was executed with ".concat(t.length," inputs"));e.forEach((function(e,n){var r=e.logicalShape,a=t[n],o=a.shape;if(!i.wf.arraysEqual(r,o))throw Error("Binary was compiled with different shapes than "+"the current args. 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this.usedTextures[a].push(s),s}return r===ig.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===ig.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===ig.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===ig.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===ig.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=o,this.log(),i}},{key:"releaseTexture",value:function(e,t,n,r){if(null!=this.freeTextures){var a=TO(n,r),o=EO(t,a,r);o in this.freeTextures||(this.freeTextures[o]=[]);var s=CO(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),c=Object(i.Ud)().get("WEBGL_DELETE_TEXTURE_THRESHOLD");-1!==c&&this._numBytesAllocated>c?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=s):(this.freeTextures[o].push(e),this.numFreeTextures++,this._numBytesFree+=s),this.numUsedTextures--;var u=this.usedTextures[o],l=u.indexOf(e);if(l<0)throw new Error("Cannot release a texture that was never provided by this texture manager");u.splice(l,1),this.log()}}},{key:"log",value:function(){if(this.logEnabled){var e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used","".concat(this.numFreeTextures," / ").concat(this.numUsedTextures),"(".concat(e,")"));var t=this._numBytesFree/this._numBytesAllocated;console.log("Bytes allocated: ".concat(this._numBytesAllocated)),console.log("Bytes unused: ".concat(this._numBytesFree," (").concat(Math.round(100*t),"%)"))}}},{key:"numBytesAllocated",get:function(){return this._numBytesAllocated}},{key:"numBytesFree",get:function(){return this._numBytesFree}},{key:"getNumUsedTextures",value:function(){return this.numUsedTextures}},{key:"getNumFreeTextures",value:function(){return this.numFreeTextures}},{key:"dispose",value:function(){var e=this;if(null!=this.freeTextures){for(var t in this.freeTextures)this.freeTextures[t].forEach((function(t){e.gpgpu.deleteMatrixTexture(t)}));for(var n in this.usedTextures)this.usedTextures[n].forEach((function(t){e.gpgpu.deleteMatrixTexture(t)}));this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}}]),e}();function CO(e,t,n,r,a){var i,s=function(e,t){switch(e){case ig.PACKED_2X2_FLOAT32:return iy(t);case ig.PACKED_2X2_FLOAT16:return oy(t);case ig.UNPACKED_FLOAT32:return ny(t);case ig.UNPACKED_FLOAT16:return ry(t);case ig.PACKED_4X1_UNSIGNED_BYTE:return ay(t);default:throw new Error("Unknown physical texture type ".concat(e))}}(t,r);if(a){var c=dg(e[0],e[1]),u=Object(o.a)(c,2);i=u[0]*u[1]}else{var l=ug(e[0],e[1]),d=Object(o.a)(l,2);i=d[0]*d[1]}return i*function(e,t){var n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F)return 16;if(t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error("Unknown internal format 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0.0) ? 0.0 : x;\n",zO=RO+"\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n",LO="return x;",PO="return 1.0 / (1.0 + exp(-1.0 * x));",BO="return x;",WO="\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n",UO="\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",VO="\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",HO="return 1.0 / (1.0 + exp(-1.0 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YO=Object(i.Ud)().getNumber("CPU_HANDOFF_SIZE_THRESHOLD");var $O=function(e){Object(Qr.a)(n,e);var t=Object(Zr.a)(n);function n(e){var r,a;if(Object(Yr.a)(this,n),(r=t.call(this)).pendingRead=new WeakMap,r.pendingDisposal=new WeakSet,r.dataRefCount=new WeakMap,r.numBytesInGPU=0,r.uploadWaitMs=0,r.downloadWaitMs=0,r.lastGlFlushTime=0,r.warnedAboutMemory=!1,r.pendingDeletes=0,r.disposed=!1,!Object(i.Ud)().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(null==e){var o=cg(Object(i.Ud)().getNumber("WEBGL_VERSION"));r.binaryCache=((a=Object(i.Ud)().getNumber("WEBGL_VERSION"))in XO||(XO[a]={}),XO[a]),r.gpgpu=new cy(o),r.canvas=o.canvas,r.gpgpuCreatedLocally=!0}else r.gpgpu=e,r.binaryCache={},r.gpgpuCreatedLocally=!1,r.canvas=e.gl.canvas;return r.textureManager=new IO(r.gpgpu),r.numMBBeforeWarning=null==Object(i.Ud)().global.screen?1024:Object(i.Ud)().global.screen.height*Object(i.Ud)().global.screen.width*window.devicePixelRatio*600/1024/1024,r.texData=new i.L(Object(ta.a)(r),Object(i.Td)()),r}return Object($r.a)(n,[{key:"nextDataId",value:function(){return n.nextDataId++}},{key:"numDataIds",value:function(){return this.texData.numDataIds()-this.pendingDeletes}},{key:"write",value:function(e,t,n){if((Object(i.Ud)().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||Object(i.Ud)().getBool("DEBUG"))&&this.checkNumericalProblems(e),"complex64"===n&&null!=e)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");var r={id:this.nextDataId()};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:ag.UPLOAD,refCount:1}),r}},{key:"refCount",value:function(e){return this.texData.has(e)?this.texData.get(e).refCount:0}},{key:"incRef",value:function(e){this.texData.get(e).refCount++}},{key:"decRef",value:function(e){this.texData.has(e)&&this.texData.get(e).refCount--}},{key:"move",value:function(e,t,n,r,a){if(Object(i.Ud)().getBool("DEBUG")&&this.checkNumericalProblems(t),"complex64"===r)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:r,values:t,usage:ag.UPLOAD,refCount:a})}},{key:"disposeIntermediateTensorInfo",value:function(e){this.disposeData(e.dataId)}},{key:"readSync",value:function(e){var t=this.texData.get(e),n=t.values,r=t.dtype,a=t.complexTensorInfos,o=t.slice,s=t.shape,c=t.isPacked;if(null!=o){var u;u=c?new GO(s,LO):new AO(s,LO);var l=this.runWebGLProgram(u,[{dataId:e,shape:s,dtype:r}],r),d=this.readSync(l.dataId);return this.disposeIntermediateTensorInfo(l),d}if(null!=n)return this.convertAndCacheOnCPU(e);if("string"===r)return n;var f,p,h=null!=this.activeTimers;if(h&&(f=i.wf.now()),"complex64"===r){var b=this.readSync(a.real.dataId),m=this.readSync(a.imag.dataId);p=i.ud.mergeRealAndImagArrays(b,m)}else p=this.getValuesFromTexture(e);return h&&(this.downloadWaitMs+=i.wf.now()-f),this.convertAndCacheOnCPU(e,p)}},{key:"read",value:function(){var e=Object(go.a)(vo.a.mark((function e(t){var n,r,a,o,s,c,u,l,d,f,p,h,b,m,v,g,y,O,x,k,w,j,S;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(!this.pendingRead.has(t)){e.next=3;break}return n=this.pendingRead.get(t),e.abrupt("return",new Promise((function(e){return n.push(e)})));case 3:if(r=this.texData.get(t),a=r.values,o=r.shape,s=r.slice,c=r.dtype,u=r.complexTensorInfos,l=r.isPacked,null==s){e.next=11;break}return d=l?new GO(o,LO):new AO(o,LO),f=this.runWebGLProgram(d,[{dataId:t,shape:o,dtype:c}],c),p=this.read(f.dataId),this.disposeIntermediateTensorInfo(f),e.abrupt("return",p);case 11:if(null==a){e.next=13;break}return e.abrupt("return",this.convertAndCacheOnCPU(t));case 13:if(Object(i.Ud)().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")||2!==Object(i.Ud)().getNumber("WEBGL_VERSION")){e.next=15;break}throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");case 15:if(h=null,"complex64"!==c&&Object(i.Ud)().get("WEBGL_BUFFER_SUPPORTED")&&(b=this.decode(t),v=this.texData.get(b.dataId),h=(m=this.gpgpu).createBufferFromTexture.apply(m,[v.texture].concat(Object(Vn.a)(lg(o))))),this.pendingRead.set(t,[]),"complex64"===c){e.next=21;break}return e.next=21,this.gpgpu.createAndWaitForFence();case 21:if("complex64"!==c){e.next=30;break}return e.next=24,Promise.all([this.read(u.real.dataId),this.read(u.imag.dataId)]);case 24:y=e.sent,O=y[0],x=y[1],g=i.ud.mergeRealAndImagArrays(O,x),e.next=31;break;case 30:null==h?g=this.getValuesFromTexture(t):(k=i.wf.sizeFromShape(o),g=this.gpgpu.downloadFloat32MatrixFromBuffer(h,k));case 31:return null!=b&&this.disposeIntermediateTensorInfo(b),null!=h&&pg(w=this.gpgpu.gl,(function(){return w.deleteBuffer(h)})),j=this.convertAndCacheOnCPU(t,g),S=this.pendingRead.get(t),this.pendingRead.delete(t),S.forEach((function(e){return e(j)})),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&Object(i.Td)().removeDataId(t,this),this.pendingDeletes--),e.abrupt("return",j);case 39:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}()},{key:"bufferSync",value:function(e){var t=this.readSync(e.dataId),n=t;if("string"===e.dtype)try{n=t.map((function(e){return i.wf.decodeString(e)}))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Object(i.zd)(e.shape,e.dtype,n)}},{key:"checkNumericalProblems",value:function(e){if(null!=e)for(var t=0;t<e.length;t++){var n=e[t];if(!hg(n)){if(Object(i.Ud)().getBool("WEBGL_RENDER_FLOAT32_CAPABLE"))throw Error("The value ".concat(n," cannot be represented with your ")+"current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'");throw Error("The value ".concat(n," cannot be represented on this device."))}}}},{key:"getValuesFromTexture",value:function(e){var t=this.texData.get(e),n=t.shape,r=t.dtype,a=t.isPacked,o=i.wf.sizeFromShape(n);if(Object(i.Ud)().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){var s,c=this.decode(e),u=this.texData.get(c.dataId),l=(s=this.gpgpu).downloadMatrixFromPackedTexture.apply(s,[u.texture].concat(Object(Vn.a)(lg(n)))).subarray(0,o);return this.disposeIntermediateTensorInfo(c),l}var d=Object(i.Ud)().getBool("WEBGL_PACK")&&!0===a,f=d?Rg(n):n,p=d?new Yg(f):new Xg(f),h=this.runWebGLProgram(p,[{shape:f,dtype:r,dataId:e}],"float32"),b=this.texData.get(h.dataId),m=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(b.texture,b.texShape[0],b.texShape[1]).subarray(0,o);return this.disposeIntermediateTensorInfo(h),m}},{key:"timerAvailable",value:function(){return Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}},{key:"time",value:function(){var e=Object(go.a)(vo.a.mark((function e(t){var n,r,a,o,s,c,u;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(n=this.activeTimers,r=[],a=!1,null==this.programTimersStack?(this.programTimersStack=r,a=!0):this.activeTimers.push(r),this.activeTimers=r,t(),o=i.wf.flatten(this.activeTimers.map((function(e){return e.query}))).filter((function(e){return null!=e})),s=i.wf.flatten(this.activeTimers.map((function(e){return e.name}))).filter((function(e){return null!=e})),this.activeTimers=n,a&&(this.programTimersStack=null),c={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},!(Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)){e.next=19;break}return e.next=14,Promise.all(o);case 14:u=e.sent,c.kernelMs=i.wf.sum(u),c.getExtraProfileInfo=function(){return u.map((function(e,t){return{name:s[t],ms:e}})).map((function(e){return"".concat(e.name,": ").concat(e.ms)})).join(", ")},e.next=20;break;case 19:c.kernelMs={error:"WebGL query timers are not supported in this environment."};case 20:return this.uploadWaitMs=0,this.downloadWaitMs=0,e.abrupt("return",c);case 23:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}()},{key:"memory",value:function(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}},{key:"startTimer",value:function(){return Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:i.wf.now(),endMs:null}}},{key:"endTimer",value:function(e){return Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=i.wf.now(),e)}},{key:"getQueryTime",value:function(){var e=Object(go.a)(vo.a.mark((function e(t){var n;return vo.a.wrap((function(e){for(;;)switch(e.prev=e.next){case 0:if(!(Object(i.Ud)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)){e.next=2;break}return e.abrupt("return",this.gpgpu.waitForQueryAndGetTime(t));case 2:return n=t,e.abrupt("return",n.endMs-n.startMs);case 4:case"end":return e.stop()}}),e,this)})));return function(t){return e.apply(this,arguments)}}()},{key:"disposeData",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1];if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);var n=this.texData.get(e),r=n.complexTensorInfos;return null!=r&&(this.disposeData(r.real.dataId,t),this.disposeData(r.imag.dataId,t)),this.texData.delete(e),!0}},{key:"releaseGPUData",value:function(e){var t=this.texData.get(e),n=t.texture,r=t.dtype,a=t.texShape,i=t.usage,o=t.isPacked,s=t.slice,c=s&&s.origDataId||e,u=this.dataRefCount.get(c);u>1?this.dataRefCount.set(c,u-1):(this.dataRefCount.delete(c),null!=n&&(this.numBytesInGPU-=this.computeBytes(a,r),this.textureManager.releaseTexture(n,a,i,o)));var l=this.texData.get(e);l.texture=null,l.texShape=null,l.isPacked=!1,l.slice=null}},{key:"getTexture",value:function(e){return this.uploadToGPU(e),this.texData.get(e).texture}},{key:"getDataInfo",value:function(e){return this.texData.get(e)}},{key:"shouldExecuteOnCPU",value:function(e){var t=this,n=arguments.length>1&&void 0!==arguments[1]?arguments[1]:YO;return Object(i.Ud)().getBool("WEBGL_CPU_FORWARD")&&e.every((function(e){return null==t.texData.get(e.dataId).texture&&i.wf.sizeFromShape(e.shape)<n}))}},{key:"getGPGPUContext",value:function(){return this.gpgpu}},{key:"where",value:function(e){i.ud.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");var t=e.dataSync();return KO(e.shape,t)}},{key:"packedUnaryOp",value:function(e,t,n){var r=new GO(e.shape,t),a=this.compileAndRun(r,[e],n);return Object(i.Td)().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}},{key:"abs",value:function(e){if(this.shouldExecuteOnCPU([e])&&"complex64"!==e.dtype){var t=uO(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,t)}if(Object(i.Ud)().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,DO,e.dtype);var n=new AO(e.shape,DO),r=this.compileAndRun(n,[e]);return Object(i.Td)().makeTensorFromDataId(r.dataId,r.shape,r.dtype)}},{key:"makeTensorInfo",value:function(e,t,n){var r;if("string"===t&&null!=n&&n.length>0&&i.wf.isString(n[0])){var a=n.map((function(e){return i.wf.encodeString(e)}));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}},{key:"makeOutput",value:function(e,t,n){var r=this.makeTensorInfo(e,t,n).dataId;return Object(i.Td)().makeTensorFromDataId(r,e,t,this)}},{key:"unpackTensor",value:function(e){var t=new qO(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}},{key:"packTensor",value:function(e){var t=new SO(e.shape);return this.runWebGLProgram(t,[e],e.dtype,null,!0)}},{key:"packedReshape",value:function(e,t){var n=[Eg(e.shape)].concat(Object(Vn.a)(Ag(e.shape))),r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[Eg(t)].concat(Object(Vn.a)(Ag(t))),i=new NO(a,n),o=this.runWebGLProgram(i,[r],e.dtype,null,!0);return{dataId:o.dataId,shape:t,dtype:o.dtype}}},{key:"decode",value:function(e){var t,n=this.texData.get(e),r=n.isPacked,a=n.shape,i=n.dtype,o=Rg(a);t=r?new Kg(o):new qg(o);return{dtype:i,shape:a,dataId:this.runWebGLProgram(t,[{shape:o,dtype:i,dataId:e}],i,null,!0).dataId}}},{key:"runWebGLProgram",value:function(e,t,n,r){var a=this,o=arguments.length>4&&void 0!==arguments[4]&&arguments[4],s=this.makeTensorInfo(e.outputShape,n),c=this.texData.get(s.dataId);if(e.packedOutput&&(c.isPacked=!0),e.outPackingScheme===rg.DENSE){var u=lg(e.outputShape);c.texShape=u.map((function(e){return 2*e}))}if(null!=e.outTexUsage&&(c.usage=e.outTexUsage),0===i.wf.sizeFromShape(s.shape))return c.values=i.wf.getTypedArrayFromDType(s.dtype,0),s;var l=[],d=t.map((function(t){if("complex64"===t.dtype)throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");var n=a.texData.get(t.dataId);if(null==n.texture){if(!e.packedInputs&&i.wf.sizeFromShape(t.shape)<=Object(i.Ud)().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:t.shape,texData:null,isUniform:!0,uniformValues:n.values};e.packedInputs&&(n.isPacked=!0,n.shape=t.shape)}else if(!!n.isPacked!==!!e.packedInputs)t=n.isPacked?a.unpackTensor(t):a.packTensor(t),l.push(t),n=a.texData.get(t.dataId);else if(n.isPacked&&!Dg(n.shape,t.shape)){var r=t,o=t.shape;t.shape=n.shape,t=a.packedReshape(t,o),l.push(t),n=a.texData.get(t.dataId),r.shape=o}return a.uploadToGPU(t.dataId),{shape:t.shape,texData:n,isUniform:!1}}));this.uploadToGPU(s.dataId);var f,p={shape:s.shape,texData:c,isUniform:!1},h=_y(e,d,p),b=this.getAndSaveBinary(h,(function(){return Ry(a.gpgpu,e,d,p)})),m=null!=this.activeTimers;m&&(f=this.startTimer()),Dy(this.gpgpu,b,d,p,r),l.forEach((function(e){return a.disposeIntermediateTensorInfo(e)})),m&&(f=this.endTimer(f),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(f)}));var v=Object(i.Ud)().get("WEBGL_FLUSH_THRESHOLD");if(v>0){var g=i.wf.now();g-this.lastGlFlushTime>v&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!Object(i.Ud)().getBool("WEBGL_LAZILY_UNPACK")&&c.isPacked&&!1===o){var y=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),y}return s}},{key:"compileAndRun",value:function(e,t,n,r){var a=arguments.length>4&&void 0!==arguments[4]&&arguments[4];n=n||t[0].dtype;var i=this.runWebGLProgram(e,t,n,r,a);return i}},{key:"getAndSaveBinary",value:function(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}},{key:"getTextureManager",value:function(){return this.textureManager}},{key:"dispose",value:function(){var e=this;if(!this.disposed){if(!Object(i.Ud)().getBool("IS_TEST"))Object.keys(this.binaryCache).forEach((function(t){e.gpgpu.deleteProgram(e.binaryCache[t].webGLProgram),delete e.binaryCache[t]}));this.textureManager.dispose(),null!=this.canvas&&"undefined"!==typeof HTMLCanvasElement&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0}}},{key:"floatPrecision",value:function(){var e=this;return null==this.floatPrecisionValue&&(this.floatPrecisionValue=Object(i.pf)((function(){if(!Object(i.Ud)().get("WEBGL_RENDER_FLOAT32_ENABLED")){var t=Object(i.Ud)().getBool("DEBUG");Object(i.Ud)().set("DEBUG",!1);var n=e.abs(Object(i.Pe)(1e-8)).dataSync()[0];if(Object(i.Ud)().set("DEBUG",t),n>0)return 32}return 16}))),this.floatPrecisionValue}},{key:"epsilon",value:function(){return 32===this.floatPrecision()?1e-7:1e-4}},{key:"uploadToGPU",value:function(e){var t=this.texData.get(e),n=t.shape,r=t.dtype,a=t.values,s=t.texture,c=t.usage,u=t.isPacked;if(null==s){var l,d=null!=this.activeTimers;d&&(l=i.wf.now());var f=t.texShape;if(null==f&&(f=function(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],n=Object(i.Ud)().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(t&&(n*=2,1===(e=e.map((function(t,n){return n>=e.length-2?i.wf.nearestLargerEven(e[n]):e[n]}))).length&&(e=[2,e[0]])),2!==e.length){var r=i.wf.squeezeShape(e);e=r.newShape}var a=i.wf.sizeFromShape(e);if(e.length<=1&&a<=n)return[1,a];if(2===e.length&&e[0]<=n&&e[1]<=n)return e;if(3===e.length&&e[0]*e[1]<=n&&e[2]<=n)return[e[0]*e[1],e[2]];if(3===e.length&&e[0]<=n&&e[1]*e[2]<=n)return[e[0],e[1]*e[2]];if(4===e.length&&e[0]*e[1]*e[2]<=n&&e[3]<=n)return[e[0]*e[1]*e[2],e[3]];if(4===e.length&&e[0]<=n&&e[1]*e[2]*e[3]<=n)return[e[0],e[1]*e[2]*e[3]];if(t){var s=Eg(e),c=2,u=2;if(e.length){var l=Ag(e),d=Object(o.a)(l,2);c=d[0],u=d[1]}return a=s*(c/2)*(u/2),i.wf.sizeToSquarishShape(a).map((function(e){return 2*e}))}return i.wf.sizeToSquarishShape(a)}(n,u),t.texShape=f),null!=a){var p,h=Rg(n),b=f[1],m=f[0],v=a instanceof Uint8Array;if(u){var g=dg(f[0],f[1]),y=Object(o.a)(g,2);b=y[0],m=y[1],p=new Qg(h,[m,b],v)}else p=new $g(h,[m,b],v);var O=this.makeTensorInfo([m,b],r);this.texData.get(O.dataId).usage=v?ag.PIXELS:ag.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(O.dataId),b,m,a);var x=this.runWebGLProgram(p,[O],r,null,!0),k=this.texData.get(x.dataId);t.texture=k.texture,t.texShape=k.texShape,t.isPacked=k.isPacked,t.usage=k.usage,this.disposeIntermediateTensorInfo(O),this.texData.delete(x.dataId),t.values=null,d&&(this.uploadWaitMs+=i.wf.now()-l)}else{var w=this.acquireTexture(f,c,r,u);t.texture=w}}}},{key:"convertAndCacheOnCPU",value:function(e,t){var n=this.texData.get(e),r=n.dtype;return this.releaseGPUData(e),null!=t&&(n.values=function(e,t){if("float32"===t||"complex64"===t)return e;if("int32"===t||"bool"===t){for(var n="int32"===t?new Int32Array(e.length):new Uint8Array(e.length),r=0;r<n.length;++r)n[r]=Math.round(e[r]);return n}throw new Error("Unknown dtype ".concat(t))}(t,r)),n.values}},{key:"acquireTexture",value:function(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>1024*this.numMBBeforeWarning*1024){var a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn("High memory usage in GPU: ".concat(a," MB, ")+"most likely due to a memory leak")}return this.textureManager.acquireTexture(e,t,r)}},{key:"computeBytes",value:function(e,t){return e[0]*e[1]*i.wf.bytesPerElement(t)}}]),n}(i.wb);$O.nextDataId=0;i.Od.isBrowser()&&Object(i.Ke)("webgl",(function(){return new $O}),2);var QO=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["A","B"],this.outputShape=i.ud.assertAndGetBroadcastShape(n,r),this.enableShapeUniforms=My(this.outputShape.length),this.userCode="\n      float binaryOperation(float a, float b) {\n        ".concat(t,"\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    ")},ZO=function e(t,n,r){var a=arguments.length>3&&void 0!==arguments[3]&&arguments[3];Object(Yr.a)(this,e),this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=i.ud.assertAndGetBroadcastShape(n,r);var o=this.outputShape.length;this.enableShapeUniforms=My(o);var s="";if(a)if(0===o||1===i.wf.sizeFromShape(this.outputShape))s="\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        ";else{var c=Cy(o);if(s="\n          ".concat(c," coords = getOutputCoords();\n        "),1===o)this.enableShapeUniforms?s+="\n            result.y = (coords + 1) >= outShape ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          ":s+="\n            result.y = (coords + 1) >= ".concat(this.outputShape[0]," ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          ");else{var u=jO("coords",o);this.enableShapeUniforms?s+="\n            bool nextRowOutOfBounds =\n              (".concat(u[o-2]," + 1) >= outShape[").concat(o," - 2];\n            bool nextColOutOfBounds =\n              (").concat(u[o-1]," + 1) >= outShape[").concat(o," - 1];\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          "):s+="\n            bool nextRowOutOfBounds =\n              (".concat(u[o-2]," + 1) >= ").concat(this.outputShape[o-2],";\n            bool nextColOutOfBounds =\n              (").concat(u[o-1]," + 1) >= ").concat(this.outputShape[o-1],";\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          ")}}this.userCode="\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        ".concat(t,"\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        ").concat(s,"\n\n        setOutput(result);\n      }\n    ")};function JO(e){var t=e.inputs,n=e.backend,r=t.x;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var ex={kernelName:i.rb,backendName:"webgl",kernelFunc:JO};function tx(e){var t=e.inputs,n=e.backend,r=t.real,a=t.imag,i=n.makeTensorInfo(r.shape,"complex64"),o=n.texData.get(i.dataId),s=JO({inputs:{x:r},backend:n}),c=JO({inputs:{x:a},backend:n});return o.complexTensorInfos={real:s,imag:c},i}var nx={kernelName:i.y,backendName:"webgl",kernelFunc:tx},rx="return (a < 0.) ? b * a : a;",ax="\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n";var ix={kernelName:i.zb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.alpha,s=n.makeTensorInfo([],"float32",i.wf.createScalarValue(o,"float32")),c=Object(i.Ud)().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ZO(ax,a.shape,s.shape):new QO(rx,a.shape,s.shape),u=n.runWebGLProgram(c,[a,s],a.dtype);return n.disposeIntermediateTensorInfo(s),u}},ox="return (a < 0.) ? b * a : a;",sx="\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n";var cx={kernelName:i.hc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.x,a=t.alpha,o=Object(i.Ud)().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ZO(sx,r.shape,a.shape):new QO(ox,r.shape,a.shape);return n.runWebGLProgram(o,[r,a],r.dtype)}};function ux(e){var t=e.opSnippet,n=e.packedOpSnippet,r=e.cpuKernelImpl,a=e.dtype;return function(e){var o,s=e.inputs,c=e.backend,u=s.x,l=c,d=a||u.dtype;if(l.shouldExecuteOnCPU([u])&&null!=r){var f=l.texData.get(u.dataId),p=r(f.values,d);return l.makeTensorInfo(u.shape,d,p)}return o=Object(i.Ud)().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&null!=n?new GO(u.shape,n):new AO(u.shape,t),l.runWebGLProgram(o,[u],d)}}function lx(e){var t=e.opSnippet,n=e.packedOpSnippet,r=e.checkOutOfBounds,a=void 0!==r&&r,s=e.supportsComplex,c=void 0!==s&&s,u=e.cpuKernelImpl,l=e.dtype;return function(e){var r=e.inputs,s=e.backend,d=r.a,f=r.b,p=s;if(c&&"complex64"===d.dtype){var h=p.texData.get(d.dataId),b=p.texData.get(f.dataId),m=[[h.complexTensorInfos.real,b.complexTensorInfos.real],[h.complexTensorInfos.imag,b.complexTensorInfos.imag]].map((function(e){var n=Object(o.a)(e,2),r=n[0],a=n[1],s={dataId:r.dataId,dtype:r.dtype,shape:d.shape},c={dataId:a.dataId,dtype:a.dtype,shape:f.shape},u=new QO(t,d.shape,f.shape);return p.runWebGLProgram(u,[s,c],Object(i.vf)(r.dtype,a.dtype))})),v=Object(o.a)(m,2),g=v[0],y=v[1],O=tx({inputs:{real:g,imag:y},backend:p});return p.disposeIntermediateTensorInfo(g),p.disposeIntermediateTensorInfo(y),O}var x,k=l||Object(i.vf)(d.dtype,f.dtype);if(("string"===d.dtype||"string"===f.dtype||p.shouldExecuteOnCPU([d,f]))&&null!=u){var w=p.texData.get(d.dataId).values,j=p.texData.get(f.dataId).values,S="string"===d.dtype?i.ud.fromUint8ToStringArray(w):w,N="string"===d.dtype?i.ud.fromUint8ToStringArray(j):j,I=u(d.shape,f.shape,S,N,k),C=Object(o.a)(I,2),T=C[0],E=C[1],A=p.makeTensorInfo(E,k);return p.texData.get(A.dataId).values=T,A}return x=Object(i.Ud)().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&null!=n?new ZO(n,d.shape,f.shape,a):new QO(t,d.shape,f.shape),p.runWebGLProgram(x,[d,f],k)}}function dx(e){var t=arguments.length>1&&void 0!==arguments[1]&&arguments[1];if("linear"===e)return t?BO:FO;if("relu"===e)return t?UO:MO;if("elu"===e)return t?WO:_O;if("relu6"===e)return t?VO:zO;if("prelu"===e)return t?sx:ox;if("leakyrelu"===e)return t?ax:rx;if("sigmoid"===e)return t?HO:PO;throw new Error("Activation ".concat(e," has not been implemented for the WebGL backend."))}var fx=function e(t,n,r){var a=arguments.length>3&&void 0!==arguments[3]&&arguments[3],i=arguments.length>4&&void 0!==arguments[4]&&arguments[4],o=arguments.length>5&&void 0!==arguments[5]&&arguments[5],s=arguments.length>6&&void 0!==arguments[6]?arguments[6]:null,c=arguments.length>7&&void 0!==arguments[7]&&arguments[7],u=arguments.length>8&&void 0!==arguments[8]&&arguments[8];Object(Yr.a)(this,e),this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=r;var l=a?t[1]:t[2],d=Math.ceil(l/2),f=a?"i * 2, rc.y":"rc.y, i * 2",p=i?"rc.z, i * 2":"i * 2, rc.z",h=a?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],b=i?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",v="";s&&(m=c?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          ".concat(s,"\n        }"):u?"vec4 activation(vec4 a) {\n          vec4 b = getLeakyreluAlphaAtOutCoords();\n          ".concat(s,"\n        }"):"vec4 activation(vec4 x) {\n          ".concat(s,"\n        }"),v="result = activation(result);");var g=o?"result += getBiasAtOutCoords();":"";o&&this.variableNames.push("bias"),c&&this.variableNames.push("preluActivationWeights"),u&&this.variableNames.push("leakyreluAlpha");var y="rc.x",O="rc.x";t[0]<n[0]?y="int(min(float(rc.x), ".concat(t[0]-1,".))"):n[0]<t[0]&&(O="int(min(float(rc.x), ".concat(n[0]-1,".))")),this.userCode="\n      ".concat(m,"\n\n      const float sharedDimension = ").concat(d,".0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < ").concat(d,"; i++) {\n          int batchA = ").concat(y,";\n          int batchB = ").concat(O,";\n          vec4 a = getMatrixA(batchA, ").concat(f,");\n          vec4 b = getMatrixB(batchB, ").concat(p,");\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += (").concat(h[0]," * ").concat(b[0],");\n          result += (").concat(h[1]," * ").concat(b[1],");\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        ").concat(g,"\n\n        ").concat(v,"\n\n        setOutput(result);\n      }\n    ")},px="return areal * breal - aimag * bimag;",hx="return areal * bimag + aimag * breal;",bx=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=i.ud.assertAndGetBroadcastShape(n,r),this.userCode="\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        ".concat(t,"\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    ")},mx="return a * b;";function vx(e){var t,n=e.inputs,r=e.backend,a=n.a,s=n.b,c=i.ud.upcastType(a.dtype,s.dtype);if("complex64"===a.dtype){var u=r.texData.get(a.dataId),l=r.texData.get(s.dataId),d=new bx(px,a.shape,s.shape),f=new bx(hx,a.shape,s.shape),p=[{dataId:u.complexTensorInfos.real.dataId,dtype:u.complexTensorInfos.real.dtype,shape:a.shape},{dataId:u.complexTensorInfos.imag.dataId,dtype:u.complexTensorInfos.imag.dtype,shape:a.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:s.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:s.shape}],h=r.runWebGLProgram(d,p,"float32"),b=r.runWebGLProgram(f,p,"float32"),m=tx({inputs:{real:h,imag:b},backend:r});return r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(b),m}if(r.shouldExecuteOnCPU([a,s])){var v=r.texData.get(a.dataId),g=r.texData.get(s.dataId),y=rO(a.shape,s.shape,v.values,g.values,c),O=Object(o.a)(y,2),x=O[0],k=O[1],w=r.makeTensorInfo(k,c);return r.texData.get(w.dataId).values=x,w}return t=Object(i.Ud)().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ZO(mx,a.shape,s.shape):new QO(mx,a.shape,s.shape),r.runWebGLProgram(t,[a,s],c)}var gx={kernelName:i.Vb,backendName:"webgl",kernelFunc:vx};function yx(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.shape,s=n,c=i.wf.sizeFromShape(a.shape),u=i.wf.inferFromImplicitShape(o,c),l=i.wf.sizeFromShape(u);i.wf.assert(c===l,(function(){return"The new shape (".concat(u,") has ").concat(l," elements and the old ")+"shape (".concat(a.shape,") has ").concat(c," elements. The new shape and old ")+"shape must have the same number of elements."}));var d=s.texData.get(a.dataId);return!d.isPacked||Dg(a.shape,u)||null!==d.texture&&Dg(d.shape,u)?(s.incRef(a.dataId),{dataId:a.dataId,shape:u,dtype:a.dtype}):function(e,t,n){var r=[Eg(e.shape)].concat(Object(Vn.a)(Ag(e.shape))),a={dtype:e.dtype,shape:r,dataId:e.dataId},i=[Eg(t)].concat(Object(Vn.a)(Ag(t))),o=new NO(i,r),s=n.runWebGLProgram(o,[a],e.dtype,null,!0);return{dataId:s.dataId,shape:t,dtype:s.dtype}}(a,u,s)}var Ox={kernelName:i.pc,backendName:"webgl",kernelFunc:yx},xx=function e(t,n){Object(Yr.a)(this,e),this.variableNames=["x"];var r=t.windowSize,a=t.batchSize,o=t.inSize,s=t.outSize;this.outputShape=[a,s];var c=4*Math.floor(r/4),u=r%4,l="sumValue += dot(values, ones);";if(null!=n){var d=1/n;l="sumValue += dot(values * ".concat(i.wf.isInt(d)?d.toPrecision(2):d,", ones);")}var f="";o%r>0&&(f="\n        if (inIdx < 0 || inIdx >= ".concat(o,") {\n          return 0.0;\n        }\n      ")),this.userCode="\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        ".concat(f,"\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ").concat(r,";\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < ").concat(c,"; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          ").concat(l,"\n        }\n\n        int inIdx = inOffset + ").concat(c,";\n        if (").concat(1===u,") {\n          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);\n\n          ").concat(l,"\n        } else if (").concat(2===u,") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1), 0.0, 0.0);\n\n          ").concat(l,"\n        } else if (").concat(3===u,") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2), 0.0);\n\n          ").concat(l,"\n        }\n        setOutput(sumValue);\n      }\n    ")},kx=function e(t,n){Object(Yr.a)(this,e),this.variableNames=["x"];var r=t.windowSize,a=t.batchSize,i=t.inSize,o=t.outSize;this.outputShape=[a,o];var s="0.0",c="";"prod"===n?s="1.0":"min"===n?(s="1.0 / 1e-20",c="min"):"max"===n&&(s="-1.0 / 1e-20",c="max");var u="".concat(n,"(").concat(n,"(").concat(n,"(")+"minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"sum"===n?u="sumValue":"prod"===n?u="prodValue":"all"===n?u="allValue":"any"===n&&(u="anyValue");var l=4*Math.floor(r/4),d=r%4,f="\n      if (".concat("sum"===n,") {\n        sumValue += dot(values, ones);\n      } else if (").concat("prod"===n,") {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = ").concat(c,"(values, minMaxValue);\n        if (").concat("min"===n," || ").concat("max"===n,") {\n          minMaxValue = ").concat(c,"(values, minMaxValue);\n          bvec4 isNaN = isnan(values);\n          if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {\n            minMaxValue = vec4(NAN);\n          }\n        }\n      }\n    "),p="vec4";"all"===n?(s="1.0",f="\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      ",p="bvec4"):"any"===n&&(s="0.0",f="\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      ",p="bvec4");var h="";i%r>0&&(h="\n        if (inIdx < 0 || inIdx >= ".concat(i,") {\n          return initializationValue;\n        }\n      ")),this.userCode="\n      const float initializationValue = ".concat(s,";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        ").concat(h,"\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ").concat(r,";\n\n        vec4 minMaxValue = vec4(").concat(s,");\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < ").concat(l,"; i += 4) {\n          int inIdx = inOffset + i;\n          ").concat(p," values = ").concat(p,"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          ").concat(f,"\n        }\n\n        int inIdx = inOffset + ").concat(l,";\n        if (").concat(1===d,") {\n          ").concat(p," values = ").concat(p,"(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          ").concat(f,"\n        } else if (").concat(2===d,") {\n          ").concat(p," values = ").concat(p,"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          ").concat(f,"\n        } else if (").concat(3===d,") {\n          ").concat(p," values = ").concat(p,"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          ").concat(f,"\n        }\n        setOutput(").concat(u,");\n      }\n    ")};function wx(e,t,n,r){for(var a=function(e){for(var t=[];0===t.length||1!==t[t.length-1].outSize;){var n=t.length?t[t.length-1].outSize:e[1],r=i.ud.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}(e.shape),o=e,s=0;s<a.length;s++){var c,u=a[s],l=u.inSize,d=u.windowSize,f=u.outSize,p=void 0;p="mean"===n?0===s?new xx({windowSize:d,inSize:l,batchSize:e.shape[0],outSize:f},l):new xx({windowSize:d,inSize:l,batchSize:e.shape[0],outSize:f}):new kx({windowSize:d,inSize:l,batchSize:e.shape[0],outSize:f},n),c=o,o=r.runWebGLProgram(p,[o],t),c.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(c)}return o}var jx=function e(t,n){Object(Yr.a)(this,e),this.variableNames=["A"];for(var r=new Array(t.length),a=0;a<r.length;a++)r[a]=t[n[a]];this.outputShape=r,this.rank=r.length;var i=Cy(this.rank),o=function(e){var t=e.length;if(t>6)throw Error("Transpose for rank ".concat(t," is not yet supported"));for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t),a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}(n);this.userCode="\n    void main() {\n      ".concat(i," resRC = getOutputCoords();\n      setOutput(getA(").concat(o,"));\n    }\n    ")};var Sx=function e(t,n){Object(Yr.a)(this,e),this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;for(var r=new Array(t.length),a=0;a<r.length;a++)r[a]=t[n[a]];if(this.outputShape=r,this.rank=r.length,this.rank>6)throw Error("Packed transpose for rank ".concat(this.rank," is not yet supported."));for(var i=Cy(this.rank),o=wO("rc",this.rank),s=new Array(this.rank),c=0;c<n.length;c++)s[n[c]]=o[c];var u="vec2(".concat(s.slice(-2).join(),")"),l="++".concat(o[this.rank-1]," < ").concat(r[this.rank-1]),d="getChannel(getA(".concat(s.join(),"), ").concat(u,")");this.userCode="\n    void main() {\n      ".concat(i," rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = ").concat(d,";\n      if(").concat(l,") {\n        result[1] = ").concat(d,";\n      }\n      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g=i.wf.sizeFromShape(m),y=yx({inputs:{x:f},attrs:{shape:[i.wf.sizeFromShape(e.shape)/g,g]},backend:r}),O=wx(y,Object(i.jf)(e.dtype),"sum",r),x=yx({inputs:{x:O},attrs:{shape:v},backend:r});return r.disposeIntermediateTensorInfo(y),r.disposeIntermediateTensorInfo(O),d&&r.disposeIntermediateTensorInfo(f),x}(t.x,r.axis,r.keepDims,n)}var Cx={kernelName:i.Yc,backendName:"webgl",kernelFunc:Ix};function Tx(e){for(var t,n=e.inputs,r=e.backend,a=e.attrs,i=n.x,o=a.perm,s=r,c=i.shape.length,u=new Array(c),l=0;l<u.length;l++)u[l]=i.shape[o[l]];if(s.shouldExecuteOnCPU([i])){var d=s.texData.get(i.dataId).values,f=xO(d,i.shape,i.dtype,o,u);t=s.makeTensorInfo(u,i.dtype),s.texData.get(t.dataId).values=f}else t=Nx(i,o,s);return t}var Ex={kernelName:i.gd,backendName:"webgl",kernelFunc:Tx};function Ax(e){var t=e.a,n=e.b,r=e.transposeA,a=e.transposeB,o=e.backend,s=e.bias,c=void 0===s?null:s,u=e.preluActivationWeights,l=void 0===u?null:u,d=e.leakyreluAlpha,f=void 0===d?0:d,p=e.activation,h=void 0===p?null:p,b=t.shape.length,m=n.shape.length,v=r?t.shape[b-2]:t.shape[b-1],g=a?n.shape[m-1]:n.shape[m-2],y=r?t.shape[b-1]:t.shape[b-2],O=a?n.shape[m-2]:n.shape[m-1],x=t.shape.slice(0,-2),k=n.shape.slice(0,-2),w=i.wf.sizeFromShape(x),j=i.wf.sizeFromShape(k),S=w===j||1===w||1===j;i.wf.assert(b>=2&&m>=2&&S,(function(){return"Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. 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V=1===O?2:1,H=B;W&&(H=yx({inputs:{x:B},backend:o,attrs:{shape:[F,1,D]}}),R.push(H));var G=vx({inputs:{a:U,b:H},backend:o});I=Ix({inputs:{x:G},backend:o,attrs:{axis:V,keepDims:!0}}),R.push(G)}else{var q=Object(i.vf)(t.dtype,n.dtype),K=new fx(C,T,[F,y,O],r,a,_,L,M,z),X=[E,A];if(null!=c&&X.push(c),M&&X.push(l),z){var Y=o.makeTensorInfo([],"float32",i.wf.createScalarValue(f,"float32"));X.push(Y),R.push(Y)}I=o.runWebGLProgram(K,X,q)}var $=yx({inputs:{x:I},backend:o,attrs:{shape:N}});R.push(I);for(var Q=0,Z=R;Q<Z.length;Q++){var J=Z[Q];o.disposeIntermediateTensorInfo(J)}return $}var Rx={kernelName:i.ld,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.a,i=t.b,o=t.bias,s=t.preluActivationWeights,c=r.transposeA,u=r.transposeB,l=r.activation;return Ax({a:a,b:i,transposeA:c,transposeB:u,backend:n,bias:o,preluActivationWeights:s,leakyreluAlpha:r.leakyreluAlpha,activation:l})}},Fx="return abs(x);";var Dx={kernelName:i.a,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=n.x;if(r.shouldExecuteOnCPU([a])&&"complex64"!==a.dtype){var o=r.texData.get(a.dataId),s=uO(o.values);return r.makeTensorInfo(a.shape,a.dtype,s)}return t=Object(i.Ud)().getBool("WEBGL_PACK_UNARY_OPERATIONS")?new GO(a.shape,Fx):new AO(a.shape,Fx),r.runWebGLProgram(t,[a],a.dtype)}},_x=ux({opSnippet:"if (isnan(x)) return x;\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return acos(x);\n"}),Mx={kernelName:i.b,backendName:"webgl",kernelFunc:_x},zx=ux({opSnippet:"if (isnan(x)) return x;\n  if (x < 1.0) return NAN;\nreturn log(x + sqrt(x * x - 1.0));"}),Lx={kernelName:i.c,backendName:"webgl",kernelFunc:zx},Px="return a + b;",Bx=lx({opSnippet:Px,packedOpSnippet:Px,supportsComplex:!0,cpuKernelImpl:zy}),Wx={kernelName:i.d,backendName:"webgl",kernelFunc:Bx},Ux=function e(t,n){Object(Yr.a)(this,e),this.outputShape=[],this.outputShape=t,this.variableNames=n.map((function(e,t){return"T".concat(t)}));var r=[];this.variableNames.forEach((function(e){r.push("float v".concat(e," = get").concat(e,"AtOutCoords();"))}));var a=this.variableNames.map((function(e){return"v".concat(e)})).join(" + ");this.userCode="\n      void main() {\n        ".concat(r.join("\n        "),"\n\n        float result = ").concat(a,";\n        setOutput(result);\n      }\n    ")},Vx=function e(t,n){Object(Yr.a)(this,e),this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.variableNames=n.map((function(e,t){return"T".concat(t)}));var r=[];this.variableNames.forEach((function(e){r.push("vec4 v".concat(e," = get").concat(e,"AtOutCoords();"))}));var a=this.variableNames.map((function(e){return"v".concat(e)})).join(" + ");this.userCode="\n      void main() {\n        ".concat(r.join("\n        "),"\n\n        vec4 result = ").concat(a,";\n        setOutput(result);\n      }\n    ")};var Hx={kernelName:i.e,backendName:"webgl",kernelFunc:function e(t){var n=t.inputs,r=t.backend,a=n;if(1===a.length)return JO({inputs:{x:a[0]},backend:r});if(a.length>Object(i.Ud)().get("WEBGL_MAX_TEXTURES_IN_SHADER")){var o=Math.floor(a.length/2),s=e({inputs:a.slice(0,o),backend:r}),c=e({inputs:a.slice(o),backend:r});return e({inputs:[s,c],backend:r})}var u=a.map((function(e){return e.dtype})).reduce((function(e,t){return Object(i.vf)(e,t)})),l=a.map((function(e){return e.shape})),d=Object(i.Ud)().getBool("WEBGL_PACK")?new Vx(a[0].shape,l):new Ux(a[0].shape,l);return r.runWebGLProgram(d,a,u)}};var Gx={kernelName:i.f,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.axis,c=r.keepDims,u=a.shape.length,l=i.wf.parseAxisParam(s,a.shape),d=l,f=i.ud.getAxesPermutation(d,u),p=a;null!=f&&(p=Tx({inputs:{x:a},backend:n,attrs:{perm:f}}),d=i.ud.getInnerMostAxes(d.length,u)),i.ud.assertAxesAreInnerMostDims("all",d,u);var h,b=i.ud.computeOutAndReduceShapes(p.shape,d),m=Object(o.a)(b,2),v=m[0],g=m[1],y=yx({inputs:{x:p},backend:n,attrs:{shape:[-1,i.wf.sizeFromShape(g)]}}),O=wx(y,y.dtype,"all",n);return h=yx(c?{inputs:{x:O},backend:n,attrs:{shape:i.ud.expandShapeToKeepDim(v,l)}}:{inputs:{x:O},backend:n,attrs:{shape:v}}),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(O),null!=f&&n.disposeIntermediateTensorInfo(p),h}};var qx={kernelName:i.g,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.axis,c=r.keepDims,u=a.shape.length,l=i.wf.parseAxisParam(s,a.shape),d=l,f=i.ud.getAxesPermutation(d,u),p=a;null!=f&&(p=Tx({inputs:{x:a},backend:n,attrs:{perm:f}}),d=i.ud.getInnerMostAxes(d.length,u)),i.ud.assertAxesAreInnerMostDims("any",d,u);var h,b=i.ud.computeOutAndReduceShapes(p.shape,d),m=Object(o.a)(b,2),v=m[0],g=m[1],y=yx({inputs:{x:p},backend:n,attrs:{shape:[-1,i.wf.sizeFromShape(g)]}}),O=wx(y,y.dtype,"any",n);return h=yx(c?{inputs:{x:O},backend:n,attrs:{shape:i.ud.expandShapeToKeepDim(v,l)}}:{inputs:{x:O},backend:n,attrs:{shape:v}}),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(O),null!=f&&n.disposeIntermediateTensorInfo(p),h}},Kx=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["A"];var a=t.windowSize,i=t.batchSize,o=t.outSize;r||this.variableNames.push("bestIndicesA"),this.outputShape=[i,o];var s="max"===n?">":"<",c=r?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ".concat(a,";\n\n        int bestIndex = inOffset;\n        float bestValue = getA(batch, bestIndex);\n\n        for (int i = 0; i < ").concat(a,"; i++) {\n          int inIdx = ").concat(c,";\n          float candidate = getA(batch, inIdx);\n          if (candidate ").concat(s," bestValue) {\n            bestValue = candidate;\n            bestIndex = inIdx;\n          }\n        }\n        setOutput(float(bestIndex));\n      }\n    ")},Xx=function e(t,n,r,a){Object(Yr.a)(this,e),this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,i.wf.assert(t.length>2,(function(){return"Packed arg".concat(r.charAt(0).toUpperCase()+r.slice(1)," supports only inputs with rank above 2.")}));var o=t[t.length-1],s=Math.ceil(o/n);this.outputShape=t.slice(0,-1),s>1&&this.outputShape.push(s),a||this.variableNames.push("bestIndicesA");var c,u,l=this.outputShape,d=l.length,f=Cy(d),p=jO("coords",d);if(1===s){var h=Cy(u=d+1);c="\n        ".concat(h," sourceLocR = ").concat(h,"(").concat(p.join(),", 0);\n        ++").concat(p[d-1],";\n        ").concat(h," sourceLocG = ").concat(h,"(").concat(p.join(),", 0);\n        ++").concat(p[d-2],";\n        ").concat(h," sourceLocA = ").concat(h,"(").concat(p.join(),", 0);\n        --").concat(p[d-1],";\n        ").concat(h," sourceLocB = ").concat(h,"(").concat(p.join(),", 0);\n        --").concat(p[d-2],";")}else u=d,c="\n        ".concat(f," sourceLocR = coords;\n        ++").concat(p[d-1],";\n        ").concat(f," sourceLocG = coords;\n        ++").concat(p[d-2],";\n        ").concat(f," sourceLocA = coords;\n        --").concat(p[d-1],";\n        ").concat(f," sourceLocB = coords;\n        --").concat(p[d-2],";");var b=["x","y","z","w","u","v"].slice(0,u),m="."+b[u-1],v=b.map((function(e){return"int "+e})),g=jO("sourceLocR",u-1).concat("inIdx.r"),y=jO("sourceLocG",u-1).concat("inIdx.g"),O=jO("sourceLocB",u-1).concat("inIdx.b"),x=jO("sourceLocA",u-1).concat("inIdx.a"),k="max"===r?"greaterThan":"lessThan",w=a?"":"\n          inIdx = round(vec4(getBestIndicesAChannel(".concat(g.join(),"),\n                             getBestIndicesAChannel(").concat(y.join(),"),\n                             getBestIndicesAChannel(").concat(O.join(),"),\n                             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s=[],c=i.ud.computeOutAndReduceShapes(t.shape,a),u=Object(o.a)(c,2),l=u[0],d=u[1],f=i.wf.sizeFromShape(d),p=yx({inputs:{x:t},backend:e,attrs:{shape:[-1,f]}});s.push(p);var h=Yx(e,p,r);s.push(h);var b=yx({inputs:{x:h},backend:e,attrs:{shape:l}});return s.forEach((function(t){return e.disposeIntermediateTensorInfo(t)})),b}return $x(e,t,r)}var Zx={kernelName:i.h,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.axis,s=i.wf.parseAxisParam(o,a.shape),c=i.ud.getAxesPermutation(s,a.shape.length),u=a,l=[];null!=c&&(u=Tx({inputs:{x:a},backend:n,attrs:{perm:c}}),l.push(u),s=i.ud.getInnerMostAxes(s.length,u.shape.length)),i.ud.assertAxesAreInnerMostDims("argMax",[s[0]],u.shape.length);var d=Qx(n,u,s[0],"max");return l.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),d}};var Jx={kernelName:i.i,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.axis,s=i.wf.parseAxisParam(o,a.shape),c=i.ud.getAxesPermutation(s,a.shape.length),u=a,l=[];null!=c&&(u=Tx({inputs:{x:a},backend:n,attrs:{perm:c}}),l.push(u),s=i.ud.getInnerMostAxes(s.length,u.shape.length)),i.ud.assertAxesAreInnerMostDims("argMin",[s[0]],u.shape.length);var d=Qx(n,u,s[0],"min");return l.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),d}},ek=ux({opSnippet:"if (isnan(x)) return x;\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return asin(x);\n"}),tk={kernelName:i.j,backendName:"webgl",kernelFunc:ek},nk=ux({opSnippet:"if (isnan(x)) return x;return log(x + sqrt(x * x + 1.0));"}),rk={kernelName:i.k,backendName:"webgl",kernelFunc:nk},ak=ux({opSnippet:"if (isnan(x)) return x;\n  return atan(x);\n"}),ik={kernelName:i.l,backendName:"webgl",kernelFunc:ak},ok=lx({opSnippet:"\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return atan(a, b);\n",packedOpSnippet:"\n  vec4 result = atan(a, b);\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n"}),sk={kernelName:i.m,backendName:"webgl",kernelFunc:ok},ck=ux({opSnippet:"if (isnan(x)) return x;\n  if ((x < -1.0) || (x > 1.0)) return NAN;\nreturn (log(1.0 + x) - log(1.0 - x)) / 2.0;"}),uk={kernelName:i.n,backendName:"webgl",kernelFunc:ck},lk=function e(t,n,r){var a=arguments.length>3&&void 0!==arguments[3]&&arguments[3],i=arguments.length>4&&void 0!==arguments[4]&&arguments[4];if(Object(Yr.a)(this,e),this.variableNames=["x"],"avg"===n&&r)throw new Error("Cannot compute positions for average pool.");var o=t.filterWidth,s=t.strideHeight,c=t.strideWidth,u=t.dilationHeight,l=t.dilationWidth,d=t.effectiveFilterHeight,f=t.effectiveFilterWidth,p=t.padInfo.top,h=t.padInfo.left;this.outputShape=t.outShape;var b="avg"===n,m="((batch  * ".concat(t.inHeight," + xR) * ").concat(t.inWidth," + xC) * ").concat(t.inChannels," + d"),v="(xR * ".concat(t.inWidth," + xC) * ").concat(t.inChannels," + d"),g="0.0";if(b||(g="-1.0 / 1e-20"),r){var y=">=";this.userCode="\n        const ivec2 strides = ivec2(".concat(s,", ").concat(c,");\n        const ivec2 pads = ivec2(").concat(p,", ").concat(h,");\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < ").concat(d,";\n              wR += ").concat(u,") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= ").concat(t.inHeight,") {\n              continue;\n            }\n\n            for (int wC = 0; wC < ").concat(f,";\n                wC += ").concat(l,") {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= ").concat(t.inWidth,") {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value ").concat(y," currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = ").concat(a?i?m:v:"wR * ".concat(f," + wC"),";\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ")}else{var O="max",x="".concat(n,"(").concat(n,"(").concat(n,"(")+"minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===n&&(x="avgValue / count");var k=4*Math.floor(o/4),w=o%4,j="\n      if (".concat(b,") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = ").concat(O,"(values, minMaxValue);\n      }\n    ");this.userCode="\n      const ivec2 strides = ivec2(".concat(s,", ").concat(c,");\n      const ivec2 pads = ivec2(").concat(p,", ").concat(h,");\n      const float initializationValue = ").concat(g,";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= ").concat(t.inWidth,") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(").concat(g,");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < ").concat(d,";\n            wR += ").concat(u,") {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= ").concat(t.inHeight,") {\n            continue;\n          }\n\n          for (int wC = 0; wC < ").concat(k,"; wC += 4) {\n            int xC = xCCorner + wC * ").concat(l,";\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ").concat(l,", d),\n              getValue(batch, xR, xC + 2 * ").concat(l,", d),\n              getValue(batch, xR, xC + 3 * ").concat(l,", d)\n            );\n\n            ").concat(j,"\n          }\n\n          int xC = xCCorner + ").concat(k,";\n          if (").concat(1===w,") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            ").concat(j,"\n          } else if (").concat(2===w,") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ").concat(l,", d),\n              initializationValue,\n              initializationValue\n            );\n\n            ").concat(j,"\n          } else if (").concat(3===w,") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ").concat(l,", d),\n              getValue(batch, xR, xC + 2 * ").concat(l,", d),\n              initializationValue\n            );\n\n            ").concat(j,"\n          }\n        }\n        setOutput(").concat(x,");\n      }\n    ")}},dk=function e(t,n,r){var a=arguments.length>3&&void 0!==arguments[3]&&arguments[3],i=arguments.length>4&&void 0!==arguments[4]&&arguments[4];if(Object(Yr.a)(this,e),this.variableNames=["x"],"avg"===n&&r)throw new Error("Cannot compute positions for average pool.");var o=t.filterWidth,s=t.strideDepth,c=t.strideHeight,u=t.strideWidth,l=t.dilationDepth,d=t.dilationHeight,f=t.dilationWidth,p=t.effectiveFilterDepth,h=t.effectiveFilterHeight,b=t.effectiveFilterWidth,m=t.padInfo.front,v=t.padInfo.top,g=t.padInfo.left;this.outputShape=t.outShape;var y="avg"===n,O="0.0";if(y||(O="-1.0 / 1e-20"),r){var x=">=";this.userCode="\n        const ivec3 strides =\n            ivec3(".concat(s,", ").concat(c,", ").concat(u,");\n        const ivec3 pads = ivec3(").concat(m,", ").concat(v,", ").concat(g,");\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < ").concat(p,";\n              wD += ").concat(l,") {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= ").concat(t.inDepth,") {\n              continue;\n            }\n\n            for (int wR = 0; wR < ").concat(h,";\n                wR += ").concat(d,") {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= ").concat(t.inHeight,") {\n                continue;\n              }\n\n              for (int wC = 0; wC < ").concat(b,";\n                  wC += ").concat(f,") {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= ").concat(t.inWidth,") {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value ").concat(x," currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;\n                  minMaxPosition = ").concat(a?i?"(((batch * ".concat(t.inDepth," + xD) * ").concat(t.inHeight," + xR) * ").concat(t.inWidth," + xC) * ").concat(t.inChannels," + ch"):"((xD * ".concat(t.inHeight," + xR) * ").concat(t.inWidth," + xC) * ").concat(t.inChannels," + ch"):"wD * ".concat(h," * ").concat(b," +\n                      wR * ").concat(b," + wC"),";\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ")}else{var k="max",w="".concat(n,"(").concat(n,"(").concat(n,"(")+"minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===n&&(w="avgValue / count");var j=4*Math.floor(o/4),S=o%4,N="\n      if (".concat(y,") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = ").concat(k,"(values, minMaxValue);\n      }\n    ");this.userCode="\n      const ivec3 strides =\n        ivec3(".concat(s,", ").concat(c,", ").concat(u,");\n      const ivec3 pads = ivec3(").concat(m,", ").concat(v,", ").concat(g,");\n      const float initializationValue = ").concat(O,";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= ").concat(t.inWidth,") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(").concat(O,");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < ").concat(p,";\n            wD += ").concat(l,") {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= ").concat(t.inDepth,") {\n            continue;\n          }\n\n          for (int wR = 0; wR < ").concat(h,";\n            wR += ").concat(d,") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= ").concat(t.inHeight,") {\n              continue;\n            }\n\n            for (int wC = 0; wC < ").concat(j,"; wC += 4) {\n              int xC = xCCorner + wC * ").concat(f,";\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ").concat(f,", ch),\n                getValue(batch, xD, xR, xC + 2 * ").concat(f,", ch),\n                getValue(batch, xD, xR, xC + 3 * ").concat(f,", ch)\n              );\n\n              ").concat(N,"\n            }\n\n            int xC = xCCorner + ").concat(j,";\n            if (").concat(1===S,") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              ").concat(N,"\n            } else if (").concat(2===S,") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ").concat(f,", ch),\n                initializationValue,\n                initializationValue\n              );\n\n              ").concat(N,"\n            } else if (").concat(3===S,") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ").concat(f,", ch),\n                getValue(batch, xD, xR, xC + 2 * ").concat(f,", ch),\n                initializationValue\n              );\n\n              ").concat(N,"\n            }\n          }\n          setOutput(").concat(w,");\n        }\n      }\n    ")}};var fk={kernelName:i.o,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x;Pg(a,"avgPool");var o=r.filterSize,s=r.strides,c=r.pad,u=r.dimRoundingMode;i.wf.assert(i.ud.eitherStridesOrDilationsAreOne(s,1),(function(){return"Error in avgPool: Either strides or dilations must be 1. "+"Got strides ".concat(s," and dilations '").concat(1,"'")}));var l=i.ud.computePool2DInfo(a.shape,o,s,1,c,u);if(1===l.filterWidth&&1===l.filterHeight&&i.wf.arraysEqual(l.inShape,l.outShape))return JO({inputs:{x:a},backend:n});var d=new lk(l,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}};var pk={kernelName:i.p,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.filterSize,s=r.strides,c=r.pad,u=r.dimRoundingMode,l=r.dataFormat,d=i.ud.computePool3DInfo(a.shape,o,s,[1,1,1],c,u,l),f=new dk(d,"avg",!1);return n.runWebGLProgram(f,[a],"float32")}},hk=function e(t){Object(Yr.a)(this,e),this.variableNames=["dy"],this.outputShape=t.inShape;var n=t.filterHeight,r=t.filterWidth,a=t.strideHeight,i=t.strideWidth,o=t.dilationHeight,s=t.dilationWidth,c=t.effectiveFilterHeight,u=t.effectiveFilterWidth,l=c-1-t.padInfo.top,d=u-1-t.padInfo.left,f=1/(n*r);this.userCode="\n      const ivec2 pads = ivec2(".concat(l,", ").concat(d,");\n      const float avgMultiplier = float(").concat(f,");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ").concat(c,";\n            wR += ").concat(o,") {\n          float dyR = float(dyRCorner + wR) / ").concat(a,".0;\n\n          if (dyR < 0.0 || dyR >= ").concat(t.outHeight,".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < ").concat(u,";\n            wC+= ").concat(s,") {\n            float dyC = float(dyCCorner + wC) / ").concat(i,".0;\n\n            if (dyC < 0.0 || dyC >= ").concat(t.outWidth,".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")},bk=function e(t){Object(Yr.a)(this,e),this.variableNames=["dy"],this.outputShape=t.inShape;var n=t.filterDepth,r=t.filterHeight,a=t.filterWidth,i=t.strideDepth,o=t.strideHeight,s=t.strideWidth,c=t.dilationDepth,u=t.dilationHeight,l=t.dilationWidth,d=t.effectiveFilterDepth,f=t.effectiveFilterHeight,p=t.effectiveFilterWidth,h=d-1-t.padInfo.front,b=f-1-t.padInfo.top,m=p-1-t.padInfo.left,v=1/(n*r*a);this.userCode="\n      const ivec3 pads = ivec3(".concat(h,", ").concat(b,", ").concat(m,");\n      const float avgMultiplier = float(").concat(v,");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < ").concat(d,";\n            wD += ").concat(c,") {\n          float dyD = float(dyDCorner + wD) / ").concat(i,".0;\n\n          if (dyD < 0.0 || dyD >= ").concat(t.outDepth,".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < ").concat(f,";\n              wR += ").concat(u,") {\n            float dyR = float(dyRCorner + wR) / ").concat(o,".0;\n\n            if (dyR < 0.0 || dyR >= ").concat(t.outHeight,".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < ").concat(p,";\n                wC += ").concat(l,") {\n              float dyC = float(dyCCorner + wC) / ").concat(s,".0;\n\n              if (dyC < 0.0 || dyC >= ").concat(t.outWidth,".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")};var mk={kernelName:i.q,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,o=t.input,s=r.filterSize,c=r.strides,u=r.pad,l=r.dimRoundingMode,d=i.ud.computePool3DInfo(o.shape,s,c,[1,1,1],u,l),f=new bk(d);return n.runWebGLProgram(f,[a],o.dtype)}};var vk={kernelName:i.r,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,o=t.input,s=o;Pg([a,o],"avgPoolGrad");var c=r.filterSize,u=r.strides,l=r.pad,d=i.ud.computePool2DInfo(s.shape,c,u,1,l),f=new hk(d);return n.runWebGLProgram(f,[a],s.dtype)}};var gk={kernelName:i.s,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs;return Ax({a:t.a,b:t.b,transposeA:r.transposeA,transposeB:r.transposeB,backend:n})}},yk=function e(t,n,r,a,o,s){Object(Yr.a)(this,e),this.outputShape=[],this.variableNames=["x","mean","variance"],i.ud.assertAndGetBroadcastShape(t,n),i.ud.assertAndGetBroadcastShape(t,r);var c="0.0";null!=a&&(i.ud.assertAndGetBroadcastShape(t,a),this.variableNames.push("offset"),c="getOffsetAtOutCoords()");var u="1.0";null!=o&&(i.ud.assertAndGetBroadcastShape(t,o),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = ".concat(c,";\n        float scale = ").concat(u,";\n        float inv = scale * inversesqrt(variance + float(").concat(s,"));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    ")},Ok=function e(t,n,r,a,o,s){Object(Yr.a)(this,e),this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],i.ud.assertAndGetBroadcastShape(t,n),i.ud.assertAndGetBroadcastShape(t,r);var c="vec4(0.0)";null!=a&&(i.ud.assertAndGetBroadcastShape(t,a),this.variableNames.push("offset"),c="getOffsetAtOutCoords()");var u="vec4(1.0)";null!=o&&(i.ud.assertAndGetBroadcastShape(t,o),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        vec4 offset = ".concat(c,";\n        vec4 scale = ").concat(u,";\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4(").concat(s,"));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    ")},xk={kernelName:i.jb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.mean,s=t.variance,c=t.offset,u=t.scale;i.wf.assert(o.shape.length===s.shape.length,(function(){return"Batch normalization gradient requires mean and variance to have equal ranks."})),i.wf.assert(null==c||o.shape.length===c.shape.length,(function(){return"Batch normalization gradient requires mean and offset to have equal ranks."})),i.wf.assert(null==u||o.shape.length===u.shape.length,(function(){return"Batch normalization gradient requires mean and scale to have equal ranks."}));var l=r.varianceEpsilon;null==l&&(l=.001);var d=[a,o,s],f=null;null!=c&&(f=c.shape,d.push(c));var p=null;null!=u&&(p=u.shape,d.push(u));var h=Object(i.Ud)().getBool("WEBGL_PACK_NORMALIZATION")?new Ok(a.shape,o.shape,s.shape,f,p,l):new yk(a.shape,o.shape,s.shape,f,p,l);return n.runWebGLProgram(h,d,d[0].dtype)}},kk=function e(t){Object(Yr.a)(this,e),this.variableNames=["source"],this.outputShape=t,this.rank=t.length;var n=Cy(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];var r,a=function(e){if(1===e)return"sourceLoc";if(e<=6)return wk.slice(0,e).map((function(e){return"sourceLoc."+e})).join(",");throw Error("Slicing for rank ".concat(e," is not yet supported"))}(this.rank),i=t.map((function(e,t){return"sourceLoc.".concat(wk[t]," = start[").concat(t,"] + coords.").concat(wk[t],";")}));r="\n        ".concat(n," sourceLoc;\n        ").concat(n," coords = getOutputCoords();\n        ").concat(i.join("\n"),"\n      "),this.userCode="\n      void main() {\n        ".concat(r,"\n        setOutput(getSource(").concat(a,"));\n      }\n    ")},wk=["x","y","z","w","u","v"];var jk=function 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b=n.texData.get(a.dataId).isPacked,m=i.af.isSliceContinous(a.shape,d,f);if(b||!m){var v=Object(i.Ud)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new jk(f):new kk(f),g=[d];return n.runWebGLProgram(v,[a],a.dtype,g)}return n.uploadToGPU(a.dataId),function(e,t,n,r){var a=r.texData.get(e.dataId),o=r.makeTensorInfo(n,e.dtype),s=r.texData.get(o.dataId);Object.assign(s,a),s.refCount=1,s.shape=n,s.dtype=e.dtype;var c=i.af.computeFlatOffset(t,i.wf.computeStrides(e.shape));a.slice&&(c+=a.slice.flatOffset),s.slice={flatOffset:c,origDataId:a.slice&&a.slice.origDataId||e.dataId};var u=r.dataRefCount.get(s.slice.origDataId)||1;return r.dataRefCount.set(s.slice.origDataId,u+1),o}(a,d,f,n)}var Nk={kernelName:i.Fc,backendName:"webgl",kernelFunc:Sk},Ik={kernelName:i.t,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.blockShape,s=r.crops;i.wf.assert(a.shape.length<=4,(function(){return"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet"}));var c=o.reduce((function(e,t){return e*t})),u=i.ud.getReshaped(a.shape,o,c),l=i.ud.getPermuted(u.length,o.length),d=i.ud.getReshapedPermuted(a.shape,o,c),f=i.ud.getSliceBeginCoords(s,o.length),p=i.ud.getSliceSize(d,s,o.length),h=[],b=yx({inputs:{x:a},backend:n,attrs:{shape:u}}),m=Tx({inputs:{x:b},backend:n,attrs:{perm:l}}),v=yx({inputs:{x:m},backend:n,attrs:{shape:d}}),g=Sk({inputs:{x:v},backend:n,attrs:{begin:f,size:p}});return h.push(b),h.push(m),h.push(v),h.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),g}};var Ck={kernelName:i.u,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.weights,o=r.size,s=n.readSync(a.dataId),c=n.readSync(i.dataId),u=Ly(s,c,i.dtype,i.shape,o);return n.makeTensorInfo([o],i.dtype,u)}},Tk=lx({opSnippet:"return float(a != b);",cpuKernelImpl:iO,dtype:"bool"}),Ek={kernelName:i.ac,backendName:"webgl",kernelFunc:Tk};function Ak(e){var t=e.inputs,n=e.backend,r=t.input;return JO({inputs:{x:n.texData.get(r.dataId).complexTensorInfos.real},backend:n})}var Rk={kernelName:i.kc,backendName:"webgl",kernelFunc:Ak};var Fk={kernelName:i.v,backendName:"webgl",kernelFunc:function e(t){var n=t.inputs,r=t.backend,a=t.attrs,o=n.x,s=a.dtype;if("complex64"===s){if("complex64"===o.dtype)return JO({inputs:{x:o},backend:r});var c=i.Bf(o.shape),u=e({inputs:{x:o},backend:r,attrs:{dtype:"float32"}}),l=tx({inputs:{real:u,imag:c},backend:r});return c.dispose(),r.disposeIntermediateTensorInfo(u),l}if("complex64"===o.dtype){var d=Ak({inputs:{input:o},backend:r}),f=e({inputs:{x:d},backend:r,attrs:{dtype:s}});return r.disposeIntermediateTensorInfo(d),f}if(!i.wf.hasEncodingLoss(o.dtype,s)){var p=JO({inputs:{x:o},backend:r});return{dataId:p.dataId,shape:p.shape,dtype:s}}if("int32"===s)return function(e,t){var n=new AO(e.shape,"return float(int(x));"),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}(o,r);if("bool"===s){var h=r.makeTensorInfo([],"bool",i.wf.getTypedArrayFromDType("bool",1)),b=Tk({inputs:{a:o,b:h},backend:r});return r.disposeIntermediateTensorInfo(h),b}throw new Error("Error in Cast: failed to cast ".concat(o.dtype," to ").concat(s))}},Dk="return ceil(x);",_k=ux({opSnippet:Dk,packedOpSnippet:Dk,cpuKernelImpl:By}),Mk={kernelName:i.w,backendName:"webgl",kernelFunc:_k},zk=function e(t){Object(Yr.a)(this,e),this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=t,this.userCode="\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    "},Lk=function e(t){Object(Yr.a)(this,e),this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=t,this.userCode="\n      void 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l=n.shouldExecuteOnCPU(e);if("string"===r&&(l=!0),l){var d=e.map((function(e){var r=i.wf.sizeFromShape(e.shape.slice(t));return yx({inputs:{x:e},backend:n,attrs:{shape:[-1,r]}})})),f=d.map((function(e){return{vals:n.readSync(e.dataId),shape:e.shape}})),p=i.ud.computeOutShape(d.map((function(e){return e.shape})),1),h=1===d[0].shape[0],b=Wy(f,p,r,h),m=i.ud.computeOutShape(e.map((function(e){return e.shape})),t),v=n.makeTensorInfo(m,r,b);return d.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),v}if(e.length>Object(i.Ud)().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){var g=Math.floor(e.length/2),y=Xk(e.slice(0,g),t,n),O=Xk(e.slice(g),t,n),x=Xk([y,O],t,n);return n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(O),x}if(Object(i.Ud)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){var k=new Hk(e.map((function(e){return e.shape})),t);return n.runWebGLProgram(k,e,r)}var w=function(e,t,n){var r=i.ud.computeOutShape(e.map((function(e){return e.shape})),t);return{tensors2D:e.map((function(e){return yx({inputs:{x:e},attrs:{shape:[-1,i.wf.sizeFromShape(e.shape.slice(t))]},backend:n})})),outShape:r}}(e,t,n),j=w.tensors2D,S=w.outShape,N=new Vk(j.map((function(e){return e.shape}))),I=n.runWebGLProgram(N,j,r);j.forEach((function(e){return n.disposeIntermediateTensorInfo(e)}));var C=yx({inputs:{x:I},attrs:{shape:S},backend:n});return n.disposeIntermediateTensorInfo(I),C}function Yk(e){var t=e.inputs,n=e.backend,r=e.attrs.axis,a=i.wf.parseAxisParam(r,t[0].shape)[0],o=i.ud.computeOutShape(t.map((function(e){return e.shape})),a);if(0===i.wf.sizeFromShape(o))return n.makeTensorInfo(o,t[0].dtype,[]);var s=t.filter((function(e){return i.wf.sizeFromShape(e.shape)>0}));if(1===s.length)return JO({inputs:{x:s[0]},backend:n});var c=s.map((function(e){return e.shape}));return i.ud.assertParamsConsistent(c,a),Xk(s,a,n)}var $k={kernelName:i.A,backendName:"webgl",kernelFunc:Yk},Qk=function e(t){var n=arguments.length>1&&void 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1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if (").concat(1===b,") {\n\n              if (").concat(m,") {\n                dotProd +=\n                    getX(batch, xR, xC, ").concat(h,") *\n                    getW(wR, wC, ").concat(h,", d2);\n              } else {\n                dotProd +=\n                    getX(batch, ").concat(h,", xR, xC) *\n                    getW(wR, wC, ").concat(h,", d2);\n              }\n\n            } else if (").concat(2===b,") {\n              vec2 wValues = vec2(\n                getW(wR, wC, ").concat(h,", d2),\n                getW(wR, wC, ").concat(h," + 1, d2)\n              );\n\n              if (").concat(m,") {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, ").concat(h,"),\n                  getX(batch, xR, xC, ").concat(h," + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, ").concat(h,", xR, xC),\n                  getX(batch, ").concat(h," + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if (").concat(3===b,") {\n              vec3 wValues = vec3(\n                getW(wR, wC, ").concat(h,", d2),\n                getW(wR, wC, ").concat(h," + 1, d2),\n                getW(wR, wC, ").concat(h," + 2, d2)\n              );\n\n              if (").concat(m,") {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, ").concat(h,"),\n                  getX(batch, xR, xC, ").concat(h," + 1),\n                  getX(batch, xR, xC, ").concat(h," + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, ").concat(h,", xR, xC),\n                  getX(batch, ").concat(h," + 1, xR, xC),\n                  getX(batch, ").concat(h," + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        ").concat(k,"\n        ").concat(x,"\n        setOutput(result);\n      }\n    ")},Zk=function e(t){Object(Yr.a)(this,e),this.variableNames=["x","W"],this.outputShape=t.outShape;var n=t.padInfo.front,r=t.padInfo.top,a=t.padInfo.left,i=t.strideDepth,o=t.strideHeight,s=t.strideWidth,c=t.dilationDepth,u=t.dilationHeight,l=t.dilationWidth,d=t.filterDepth,f=t.filterHeight,p=t.filterWidth,h=4*Math.floor(t.inChannels/4),b=t.inChannels%4;this.userCode="\n      const ivec3 strides = ivec3(".concat(i,", ").concat(o,", ").concat(s,");\n      const ivec3 pads = ivec3(").concat(n,", ").concat(r,", ").concat(a,");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < ").concat(d,"; wF++) {\n          int xF = xFCorner + wF * ").concat(c,";\n\n          if (xF < 0 || xF >= ").concat(t.inDepth,") {\n            continue;\n          }\n\n          for (int wR = 0; wR < ").concat(f,"; wR++) {\n            int xR = xRCorner + wR * ").concat(u,";\n\n            if (xR < 0 || xR >= ").concat(t.inHeight,") {\n              continue;\n            }\n\n            for (int wC = 0; wC < ").concat(p,"; wC++) {\n              int xC = xCCorner + wC * ").concat(l,";\n\n              if (xC < 0 || xC >= ").concat(t.inWidth,") {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < ").concat(h,"; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if (").concat(1===b,") {\n                dotProd +=\n                  getX(batch, xF, xR, xC, ").concat(h,") *\n                  getW(wF, wR, wC, ").concat(h,", d2);\n              } else if (").concat(2===b,") {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, ").concat(h,"),\n                  getX(batch, xF, xR, xC, ").concat(h," + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, ").concat(h,", d2),\n                  getW(wF, wR, wC, ").concat(h," + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if (").concat(3===b,") {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, ").concat(h,"),\n                  getX(batch, xF, xR, xC, ").concat(h," + 1),\n                  getX(batch, xF, xR, xC, ").concat(h," + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, ").concat(h,", d2),\n                  getW(wF, wR, wC, ").concat(h," + 1, d2),\n                  getW(wF, wR, wC, ").concat(h," + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")},Jk=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var a=r.filterWidth,i=r.inChannels,o=r.strideWidth,s=r.strideHeight,c=r.padInfo,u=r.outWidth,l=r.dilationWidth,d=r.dilationHeight,f=r.dataFormat,p=c.left,h=c.top,b=i*a,m=Wg(),v="channelsLast"===f,g=v?0:1,y=v?1:2,O="",x=0;x<=1;x++)for(var k=0;k<=1;k++)O+="\n          blockIndex = rc.y + ".concat(k,";\n          pos = rc.x + ").concat(x,";\n\n          if(blockIndex < ").concat(t[1]," && pos < ").concat(t[0],") {\n            offsetY = int(blockIndex / (").concat(u,")) * ").concat(s," - ").concat(h,";\n            d0 = offsetY + ").concat(d," * (pos / ").concat(b,");\n\n            if(d0 < ").concat(n[g]," && d0 >= 0) {\n\n              offsetX = int(mod(float(blockIndex), ").concat(u,".) * ").concat(o,". - ").concat(p,".);\n              d1 = offsetX + ").concat(l," * (int(mod(float(pos), ").concat(b,".) / ").concat(i,".));\n\n              if(d1 < ").concat(n[y]," && d1 >= 0) {\n\n                ch = int(mod(float(pos), ").concat(i,".));\n\n                if (").concat(v,") {\n                  innerDims = vec2(d1, ch);\n                  result[").concat(2*x+k,"] = getChannel(\n                    getA(d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result[").concat(2*x+k,"] = getChannel(\n                    getA(ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        ");this.userCode="\n      void main() {\n        ivec2 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        ".concat(O,"\n\n        ").concat(m.output," = result;\n      }\n    ")};function ew(e){var t,n=e.x,r=e.filter,a=e.convInfo,o=e.backend,s=e.bias,c=void 0===s?null:s,u=e.preluActivationWeights,l=void 0===u?null:u,d=e.leakyreluAlpha,f=void 0===d?0:d,p=e.activation,h=void 0===p?null:p,b=n.shape,m=o.texData.get(n.dataId),v=a.inChannels,g=b[0]*b[1]*b[2],y=a.outChannels,O="channelsLast"===a.dataFormat,x=[],k=(1===g||1===y)&&v>1e3,w=b[2]%2!==0&&!!m.isPacked;if(!k&&Object(i.Ud)().getBool("WEBGL_LAZILY_UNPACK")&&Object(i.Ud)().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&w){var j=O?b[0]*b[1]*(b[2]+1):b[0]*b[2]*(b[3]+1),S={dataId:n.dataId,shape:[1,j,a.inChannels],dtype:n.dtype},N=m.shape;m.shape=m.shape.slice(),m.shape[m.shape.length-2]++,i.wf.assert(Dg(m.shape,S.shape),(function(){return"packed reshape ".concat(m.shape," to ").concat(S.shape," isn't free")}));var I=yx({inputs:{x:r},backend:o,attrs:{shape:[1,a.inChannels,a.outChannels]}});x.push(I);var C=Ax({a:S,b:I,backend:o,transposeA:false,transposeB:false,bias:c,activation:h,preluActivationWeights:l,leakyreluAlpha:f}),T=o.texData.get(C.dataId);i.wf.assert(T.isPacked,(function(){return"batchMatMul result is expected to be packed"})),m.shape=N,T.shape=a.outShape,(t=JO({inputs:{x:C},backend:o})).shape=a.outShape,x.push(C)}else{var E=yx({inputs:{x:n},backend:o,attrs:{shape:[1,O?b[0]*b[1]*b[2]:b[0]*b[2]*b[3],a.inChannels]}}),A=yx({inputs:{x:r},backend:o,attrs:{shape:[1,a.inChannels,a.outChannels]}}),R=Ax({a:E,b:A,transposeA:false,transposeB:false,backend:o,bias:c,activation:h,preluActivationWeights:l,leakyreluAlpha:f});t=yx({inputs:{x:R},backend:o,attrs:{shape:a.outShape}}),x.push(E),x.push(A),x.push(R)}for(var F=0,D=x;F<D.length;F++){var _=D[F];o.disposeIntermediateTensorInfo(_)}return t}function tw(e){var t=e.x,n=e.filter,r=e.convInfo,a=e.backend,o=e.bias,s=void 0===o?null:o,c=e.preluActivationWeights,u=void 0===c?null:c,l=e.leakyreluAlpha,d=void 0===l?0:l,f=e.activation,p=void 0===f?null:f,h=r.filterWidth,b=r.filterHeight,m=r.inChannels,v=r.outWidth,g=r.outHeight,y="channelsLast"===r.dataFormat,O=h*b*m,x=g*v,k=[O,x],w=[],j=yx({inputs:{x:t},backend:a,attrs:{shape:t.shape.slice(1)}}),S=yx({inputs:{x:n},backend:a,attrs:{shape:[1,O,i.wf.sizeFromShape(n.shape)/O]}});w.push(j),w.push(S);var N=new Jk(k,j.shape,r),I=a.runWebGLProgram(N,[j],"float32"),C=yx({inputs:{x:I},backend:a,attrs:{shape:[1,k[0],k[1]]}});w.push(I),w.push(C);var T=null!=s,E=null!=u,A="leakyrelu"===p,R=p?dx(p,!0):null,F=new fx(C.shape,S.shape,[1,x,r.outChannels],!0,!1,T,R,E,A),D=[C,S];if(s&&D.push(s),E&&D.push(u),A){var _=a.makeTensorInfo([],"float32",i.wf.createScalarValue(d,"float32"));D.push(_),w.push(_)}var M=a.runWebGLProgram(F,D,"float32"),z=yx({inputs:{x:M},backend:a,attrs:{shape:y?[1,g,v,r.outChannels]:[1,r.outChannels,g,v]}});w.push(M);for(var L=0,P=w;L<P.length;L++){var B=P[L];a.disposeIntermediateTensorInfo(B)}return z}var nw={kernelName:i.B,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=e.attrs,o=n.x,s=n.filter,c=a.strides,u=a.pad,l=a.dataFormat,d=a.dilations,f=a.dimRoundingMode,p=i.ud.convertConv2DDataFormat(l),h=i.ud.computeConv2DInfo(o.shape,s.shape,c,d,u,f,!1,p);if(1!==h.filterHeight||1!==h.filterWidth||1!==h.dilationHeight||1!==h.dilationWidth||1!==h.strideHeight||1!==h.strideWidth||"SAME"!==h.padInfo.type&&"VALID"!==h.padInfo.type)if(Object(i.Ud)().getBool("WEBGL_CONV_IM2COL")&&1===o.shape[0])t=tw({x:o,filter:s,convInfo:h,backend:r});else{var b=new Qk(h);t=r.runWebGLProgram(b,[o,s],"float32")}else t=ew({x:o,filter:s,convInfo:h,backend:r});var m=yx({inputs:{x:t},backend:r,attrs:{shape:h.outShape}});return r.disposeIntermediateTensorInfo(t),m}},rw=function e(t){Object(Yr.a)(this,e),this.variableNames=["x","dy"],this.outputShape=t.filterShape;var n=t.strideHeight,r=t.strideWidth,a=t.padInfo.top,i=t.padInfo.left,o="channelsLast"===t.dataFormat;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < ".concat(t.batchSize,"; b++) {\n          for (int yR = 0; yR < ").concat(t.outHeight,"; yR++) {\n            int xR = wR + yR * ").concat(n," - ").concat(a,";\n\n            if (xR < 0 || xR >= ").concat(t.inHeight,") {\n              continue;\n            }\n\n            for (int yC = 0; yC < ").concat(t.outWidth,"; yC++) {\n              int xC = wC + yC * ").concat(r," - ").concat(i,";\n\n              if (xC < 0 || xC >= ").concat(t.inWidth,") {\n                continue;\n              }\n\n              if (").concat(o,") {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")},aw=function e(t){Object(Yr.a)(this,e),this.variableNames=["dy","W"],this.outputShape=t.inShape;var n=t.filterHeight,r=t.filterWidth,a=t.strideHeight,i=t.strideWidth,o="channelsLast"===t.dataFormat,s=n-1-t.padInfo.top,c=r-1-t.padInfo.left,u=o?1:2,l=o?2:3,d=o?3:1;this.userCode="\n      const ivec2 pads = ivec2(".concat(s,", ").concat(c,");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[").concat(d,"];\n\n        ivec2 dyCorner = ivec2(coords[").concat(u,"], coords[").concat(l,"]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ").concat(n,"; wR++) {\n          float dyR = float(dyRCorner + wR) / ").concat(a,".0;\n\n          if (dyR < 0.0 || dyR >= ").concat(t.outHeight,".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = ").concat(n," - 1 - wR;\n\n          for (int wC = 0; wC < ").concat(r,"; wC++) {\n            float dyC = float(dyCCorner + wC) / ").concat(i,".0;\n\n            if (dyC < 0.0 || dyC >= ").concat(t.outWidth,".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = ").concat(r," - 1 - wC;\n\n            for (int d2 = 0; d2 < ").concat(t.outChannels,"; d2++) {\n\n              if (").concat(o,") {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")},iw=function e(t){Object(Yr.a)(this,e),this.variableNames=["x","dy"],this.outputShape=t.filterShape;var n=t.strideDepth,r=t.strideHeight,a=t.strideWidth,i=t.padInfo.front,o=t.padInfo.top,s=t.padInfo.left;this.userCode="\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < ".concat(t.batchSize,"; b++) {\n          for (int yF = 0; yF < ").concat(t.outDepth,"; yF++) {\n            int xF = wF + yF * ").concat(n," - ").concat(i,";\n\n            if (xF < 0 || xF >= ").concat(t.inDepth,") {\n              continue;\n            }\n\n            for (int yR = 0; yR < ").concat(t.outHeight,"; yR++) {\n              int xR = wR + yR * ").concat(r," - ").concat(o,";\n\n              if (xR < 0 || xR >= ").concat(t.inHeight,") {\n                continue;\n              }\n\n              for (int yC = 0; yC < ").concat(t.outWidth,"; yC++) {\n                int xC = wC + yC * ").concat(a," - ").concat(s,";\n\n                if (xC < 0 || xC >= ").concat(t.inWidth,") {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")},ow=function e(t){Object(Yr.a)(this,e),this.variableNames=["dy","W"],this.outputShape=t.inShape;var n=t.filterDepth,r=t.filterHeight,a=t.filterWidth,i=t.strideDepth,o=t.strideHeight,s=t.strideWidth,c=n-1-t.padInfo.front,u=r-1-t.padInfo.top,l=a-1-t.padInfo.left;this.userCode="\n      const ivec3 pads = ivec3(".concat(c,", ").concat(u,", ").concat(l,");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < ").concat(n,"; wF++) {\n          float dyF = float(dyFCorner + wF) / ").concat(i,".0;\n\n          if (dyF < 0.0 || dyF >= ").concat(t.outDepth,".0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = ").concat(n," - 1 - wF;\n\n          for (int wR = 0; wR < ").concat(r,"; wR++) {\n            float dyR = float(dyRCorner + wR) / ").concat(o,".0;\n\n            if (dyR < 0.0 || dyR >= ").concat(t.outHeight,".0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = ").concat(r," - 1 - wR;\n\n            for (int wC = 0; wC < ").concat(a,"; wC++) {\n              float dyC = float(dyCCorner + wC) / ").concat(s,".0;\n\n              if (dyC < 0.0 || dyC >= ").concat(t.outWidth,".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = ").concat(a," - 1 - wC;\n\n              for (int d2 = 0; d2 < ").concat(t.outChannels,"; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")};var sw={kernelName:i.C,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.dy,s=r.strides,c=r.pad,u=r.dataFormat,l=r.dimRoundingMode,d=r.filterShape,f=i.ud.convertConv2DDataFormat(u),p=i.ud.computeConv2DInfo(a.shape,d,s,1,c,l,!1,f),h=new rw(p);return n.runWebGLProgram(h,[a,o],"float32")}};var cw={kernelName:i.D,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,o=t.filter,s=r.inputShape,c=r.strides,u=r.pad,l=r.dataFormat,d=r.dimRoundingMode,f=i.ud.convertConv2DDataFormat(l),p=i.ud.computeConv2DInfo(s,o.shape,c,1,u,d,!1,f),h=new aw(p);return n.runWebGLProgram(h,[a,o],"float32")}};var uw={kernelName:i.E,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.filter,s=r.strides,c=r.pad,u=r.dilations,l=i.ud.computeConv3DInfo(a.shape,o.shape,s,u,c),d=new Zk(l);return n.runWebGLProgram(d,[a,o],"float32")}};var lw={kernelName:i.F,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.dy,s=r.strides,c=r.pad,u=r.filterShape,l=i.ud.computeConv3DInfo(a.shape,u,s,1,c),d=new iw(l);return n.runWebGLProgram(d,[a,o],"float32")}};var dw={kernelName:i.G,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,o=t.filter,s=r.pad,c=r.strides,u=r.inputShape,l=i.ud.computeConv3DInfo(u,o.shape,c,1,s),d=new ow(l);return n.runWebGLProgram(d,[a,o],"float32")}},fw=ux({opSnippet:"if (isnan(x)) return x;\n  return cos(x);\n"}),pw={kernelName:i.H,backendName:"webgl",kernelFunc:fw},hw=ux({opSnippet:"\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n"}),bw={kernelName:i.I,backendName:"webgl",kernelFunc:hw},mw=function e(t,n,r,a,i){Object(Yr.a)(this,e),this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];var s=Object(o.a)(t,4),c=s[0],u=s[1],l=s[2],d=s[3],f=Object(o.a)(n,1)[0],p=Object(o.a)(r,2),h=p[0],b=p[1];this.outputShape=[f,h,b,d];var m="bilinear"===a?1:0,v="".concat(u-1,".0"),g="".concat(l-1,".0"),y=h>1?["".concat((u-1)/(h-1)),"(y2-y1) * height_ratio","y1*".concat(v," + float(y)*(height_scale)")]:["0.0","0.0","0.5 * (y1+y2) * ".concat(v)],O=Object(o.a)(y,3),x=O[0],k=O[1],w=O[2],j=b>1?["".concat((l-1)/(b-1)),"(x2-x1) * width_ratio","x1*".concat(g," + float(x)*(width_scale)")]:["0.0","0.0","0.5 * (x1+x2) * ".concat(g)],S=Object(o.a)(j,3),N=S[0],I=S[1],C=S[2];this.userCode="\n      const float height_ratio = float(".concat(x,");\n      const float width_ratio = float(").concat(N,");\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n  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sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    ")},vw={kernelName:i.J,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.image,i=t.boxes,o=t.boxInd,s=r.cropSize,c=r.method,u=r.extrapolationValue,l=new mw(a.shape,i.shape,s,c,u);return n.runWebGLProgram(l,[a,i,o],"float32")}},gw=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}],this.outputShape=t;var a=t.length,i=n?"0.0":"getX(".concat(yw(a,"coords"),")"),o=t[t.length-1],s="",c="";n?(s=r?"end != ".concat(o-1):"end != 0",c=r?"end + 1":"end - 1"):(s=r?"end + pow2 < ".concat(o):"end >= pow2",c=r?"end + pow2":"end - pow2"),this.userCode="\n      void main() {\n        ".concat(Cy(a)," coords = getOutputCoords();\n        int end = ").concat(Ow(a,"coords"),";\n        float val = ").concat(i,";\n        int pow2 = int(pow(2.0, index));\n        if (").concat(s,") {\n          int idx = ").concat(c,";\n          ").concat(Ow(a,"coords")," = idx;\n          val += getX(").concat(yw(a,"coords"),");\n        }\n        setOutput(val);\n      }\n    ")};function yw(e,t){if(1===e)return"".concat(t);if(2===e)return"".concat(t,".x, ").concat(t,".y");if(3===e)return"".concat(t,".x, ").concat(t,".y, ").concat(t,".z");if(4===e)return"".concat(t,".x, ").concat(t,".y, ").concat(t,".z, ").concat(t,".w");throw Error("Cumulative sum for rank ".concat(e," is not yet supported"))}function Ow(e,t){if(1===e)return"".concat(t);if(2===e)return"".concat(t,".y");if(3===e)return"".concat(t,".z");if(4===e)return"".concat(t,".w");throw Error("Cumulative sum for rank ".concat(e," is not yet supported"))}var xw={kernelName:i.K,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.axis,s=r.exclusive,c=r.reverse,u=a.shape.length,l=i.ud.getAxesPermutation([o],u),d=a;null!=l&&(d=Tx({inputs:{x:a},backend:n,attrs:{perm:l}}));var f=i.ud.getInnerMostAxes(1,u)[0];if(f!==u-1)throw new Error("WebGL cumsum shader expects an inner-most axis=".concat(a.shape.length-1," ")+"but got axis=".concat(o));for(var p=d.shape[f],h=JO({inputs:{x:d},backend:n}),b=0;b<=Math.ceil(Math.log2(p))-1;b++){var m=new gw(d.shape,!1,c),v=[[b]],g=h;h=n.runWebGLProgram(m,[h],h.dtype,v),n.disposeIntermediateTensorInfo(g)}if(s){var y=new gw(d.shape,s,c),O=h;h=n.runWebGLProgram(y,[h],h.dtype),n.disposeIntermediateTensorInfo(O)}if(null!=l){var x=Tx({inputs:{x:h},backend:n,attrs:{perm:i.ud.getUndoAxesPermutation(l)}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),x}return h}};var kw={kernelName:i.M,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.weights,o=r.size,s=r.binaryOutput;if(1===a.shape.length){var c=n.readSync(a.dataId),u=n.readSync(i.dataId),l=Ly(c,u,i.dtype,i.shape,o);return n.makeTensorInfo([o],i.dtype,l)}if(2===a.shape.length){var d=n.bufferSync(a),f=n.bufferSync(i),p=Py(d,f,o,s);return n.makeTensorInfo(p.shape,i.dtype,p.values)}throw new Error("Error in denseBincount: input must be at most rank 2, but got rank"+"".concat(a.shape.length,"."))}},ww=function(){function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["x"],this.outputShape=[],this.outputShape=t,this.blockSize=n,this.dataFormat=r,this.userCode="\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = ".concat(this.getHeightCoordString(),";\n      int w = ").concat(this.getWidthCoordString(),";\n      int d = ").concat(this.getDepthCoordString(),";\n\n      int in_h = h / ").concat(n,";\n      int offset_h = imod(h, ").concat(n,");\n      int in_w = w / ").concat(n,";\n      int offset_w = imod(w, ").concat(n,");\n      int offset_d = (offset_h * ").concat(n," + offset_w) *\n        ").concat(this.getOutputDepthSize(),";\n      int in_d = d + offset_d;\n\n      float result = ").concat(this.getInputSamplingString(),";\n      setOutput(result);\n    }\n  ")}return Object($r.a)(e,[{key:"getHeightCoordString",value:function(){return"NHWC"===this.dataFormat?"coords[1]":"coords[2]"}},{key:"getWidthCoordString",value:function(){return"NHWC"===this.dataFormat?"coords[2]":"coords[3]"}},{key:"getDepthCoordString",value:function(){return"NHWC"===this.dataFormat?"coords[3]":"coords[1]"}},{key:"getOutputDepthSize",value:function(){return"NHWC"===this.dataFormat?this.outputShape[3]:this.outputShape[1]}},{key:"getInputSamplingString",value:function(){return"NHWC"===this.dataFormat?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}}]),e}();var jw={kernelName:i.N,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.blockSize,s=r.dataFormat;i.wf.assert(o>1,(function(){return"blockSize should be > 1 for depthToSpace, but was: ".concat(o)}));var c=a.shape[0],u="NHWC"===s?a.shape[1]:a.shape[2],l="NHWC"===s?a.shape[2]:a.shape[3],d="NHWC"===s?a.shape[3]:a.shape[1],f=u*o,p=l*o,h=d/(o*o),b=new ww("NHWC"===s?[c,f,p,h]:[c,h,f,p],o,s);return n.runWebGLProgram(b,[a],a.dtype)}},Sw=function e(t){var n=arguments.length>1&&void 0!==arguments[1]&&arguments[1],r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:null,a=arguments.length>3&&void 0!==arguments[3]&&arguments[3],i=arguments.length>4&&void 0!==arguments[4]&&arguments[4];Object(Yr.a)(this,e),this.variableNames=["x","W"],this.outputShape=t.outShape;var o=t.inHeight,s=t.inWidth,c=t.padInfo.top,u=t.padInfo.left,l=t.strideHeight,d=t.strideWidth,f=t.dilationHeight,p=t.dilationWidth,h=t.filterHeight,b=t.filterWidth,m=t.outChannels/t.inChannels,v="",g="";r&&(v=a?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          ".concat(r,"\n        }"):i?"float activation(float a) {\n          float b = getLeakyreluAlphaAtOutCoords();\n          ".concat(r,"\n        }"):"\n          float activation(float x) {\n            ".concat(r,"\n          }\n        "),g="result = activation(result);");var y=n?"result += getBiasAtOutCoords();":"";n&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),i&&this.variableNames.push("leakyreluAlpha"),this.userCode="\n      ".concat(v,"\n\n      const ivec2 strides = ivec2(").concat(l,", ").concat(d,");\n      const ivec2 pads = ivec2(").concat(c,", ").concat(u,");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / ").concat(m,";\n        int q = d2 - d1 * ").concat(m,";\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < ").concat(h,"; wR++) {\n          int xR = xRCorner + wR * ").concat(f,";\n\n          if (xR < 0 || xR >= ").concat(o,") {\n            continue;\n          }\n\n          for (int wC = 0; wC < ").concat(b,"; wC++) {\n            int xC = xCCorner + wC * ").concat(p,";\n\n            if (xC < 0 || xC >= ").concat(s,") {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n\n        float result = dotProd;\n        ").concat(y,"\n        ").concat(g,"\n        setOutput(result);\n      }\n    ")},Nw=function e(t){var n=arguments.length>1&&void 0!==arguments[1]&&arguments[1],r=arguments.length>2&&void 0!==arguments[2]?arguments[2]:null,a=arguments.length>3&&void 0!==arguments[3]&&arguments[3],o=arguments.length>4&&void 0!==arguments[4]&&arguments[4];Object(Yr.a)(this,e),this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.outShape;for(var s=t.outChannels/t.inChannels,c=t.inHeight,u=t.inWidth,l=t.padInfo.top,d=t.padInfo.left,f=t.strideHeight,p=t.strideWidth,h=t.dilationHeight,b=t.dilationWidth,m=t.filterHeight,v=t.filterWidth,g=v,y="\n      int xR; int xC; int xCOffset;\n      vec4 wTexel; vec4 previous; vec4 final;",O=0;O<v;O++)y+="\n          vec4 xTexelC".concat(2*O,";\n          int xTexelC").concat(2*O,"Ready;\n          vec4 xTexelC").concat(2*O+1,";\n          int xTexelC").concat(2*O+1,"Ready;\n          vec4 xC").concat(O,";");for(var x=0;x<m;x++){for(var k=0;k<v;k++)y+="\n          xTexelC".concat(2*k," = vec4(0.0);\n          xTexelC").concat(2*k,"Ready = 0;\n          xTexelC").concat(2*k+1," = vec4(0.0);\n          xTexelC").concat(2*k+1,"Ready = 0;\n          xC").concat(k," = vec4(0.0);");y+="\n        xR = xRCorner + ".concat(x*h,";\n        if (xR >=0 && xR < ").concat(c,") {\n      ");for(var w=0;w<(g+1)/2;w++){var j=2*w,S=j*b;if(y+="\n          xC = xCCorner + ".concat(S,";\n          "),1===p){if(j<v&&(d%2===1?(y+="\n                xCOffset = xC + 1;\n                if (xCOffset >= 0 && xCOffset < ".concat(u," && xTexelC").concat(j,"Ready == 0) {\n                  xTexelC").concat(j," = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xCOffset + 1 >= ").concat(u,") {\n                    xTexelC").concat(j,".zw = vec2(0.0);\n                  }\n                  xTexelC").concat(j,"Ready = 1;\n                }\n              "),y+=1===b&&S>0?"\n                xC".concat(j," = vec4(xTexelC").concat(j-2,".zw, xTexelC").concat(j,".xy);\n                "):"\n                  xCOffset = xC + 1 - 2;\n\n                  if (xCOffset >= 0 && xCOffset < ".concat(u,") {\n                    previous = getX(batch, xR, xCOffset, d1);\n\n                    // Need to manually clear unused channels in case\n                    // we're reading from recycled texture.\n                    if (xCOffset + 1 >= ").concat(u,") {\n                      previous.zw = vec2(0.0);\n                    }\n\n                    xC").concat(j," = vec4(previous.zw, xTexelC").concat(j,".xy);\n                  } else {\n                    xC").concat(j," = vec4(0.0, 0.0, xTexelC").concat(j,".xy);\n                  }\n                  ")):y+="\n                if (xC >= 0 && xC < ".concat(u," && xTexelC").concat(j,"Ready == 0) {\n                  xTexelC").concat(j," = getX(batch, xR, xC, d1);\n                  if (xC + 1 >= ").concat(u,") {\n                    xTexelC").concat(j,".zw = vec2(0.0);\n                  }\n                  xTexelC").concat(j,"Ready = 1;\n                }\n\n                xC").concat(j," = xTexelC").concat(j,";\n                "),S+1<v)){var N=d%2===0?i.wf.nearestLargerEven(b):b;b%2===0&&d%2===1||b%2!==0&&d%2!==1?(y+="\n                  xCOffset = xC + ".concat(d%2," + ").concat(N,";\n\n                  if (xCOffset >= 0 && xCOffset < ").concat(u," && xTexelC").concat(j+1,"Ready == 0) {\n                    xTexelC").concat(j+1," = getX(batch, xR, xCOffset, d1);\n\n                    // Need to manually clear unused channels in case\n                    // we're reading from recycled texture.\n                    if (xCOffset + 1 >= ").concat(u,") {\n                      xTexelC").concat(j+1,".zw = vec2(0.0);\n                    }\n                    xTexelC").concat(j+1,"Ready = 1;\n                  }\n                  "),b>1&&(y+="\n                    xCOffset -= 2;\n                    if (xCOffset >= 0 && xCOffset < ".concat(u," && xTexelC").concat(j,"Ready == 0) {\n                      xTexelC").concat(j," = getX(batch, xR, xCOffset, d1);\n                      xTexelC").concat(j,"Ready = 1;\n                    }\n                    ")),y+="\n                  xC".concat(j+1," = vec4(xTexelC").concat(j,".zw, xTexelC").concat(j+1,".xy);\n                  ")):y+=1===N?"\n                    xC".concat(j+1," = xTexelC").concat(j,";\n                    "):"\n                    xCOffset = xC + ".concat(N,";\n\n                    if (xCOffset >= 0 && xCOffset < ").concat(u," && xTexelC").concat(j+1,"Ready == 0) {\n                      xTexelC").concat(j+1," = getX(batch, xR, xCOffset, d1);\n                      if (xCOffset + 1 >= ").concat(u,") {\n                        xTexelC").concat(j+1,".zw = vec2(0.0);\n                      }\n                      xTexelC").concat(j+1,"Ready = 1;\n                    }\n\n                    xC").concat(j+1," = xTexelC").concat(j+1,";\n                    ")}}else S<v&&(d%2===1?(y+="\n                xCOffset = xC + 1 - ".concat(p,";\n                if(xCOffset >= 0 && xCOffset < ").concat(u," && xTexelC").concat(j,"Ready == 0) {\n                  xTexelC").concat(j," = getX(batch, xR, xCOffset, d1);\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xCOffset + 1 >= ").concat(u,") {\n                    xTexelC").concat(j,".zw = vec2(0.0);\n                  }\n                  xTexelC").concat(j,"Ready = 1;\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < ").concat(u," && xTexelC").concat(j+1,"Ready == 0) {\n                  xTexelC").concat(j+1," = getX(batch, xR, xC + 1, d1);\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xC + 2 >= ").concat(u,") {\n                    xTexelC").concat(j+1,".zw = vec2(0.0);\n                  }\n                  xTexelC").concat(j+1,"Ready = 1;\n                }\n\n                xC").concat(j," = vec4(xTexelC").concat(j,".zw, xTexelC").concat(j+1,".zw);\n              "),S+1<v&&(y+="\n                  final = vec4(0.0);\n                  xCOffset = xC + 1 + ".concat(p,";\n                  if(xCOffset >= 0 && xCOffset < ").concat(u,") {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xC").concat(j+1," = vec4(xTexelC").concat(j+1,".xy, final.xy);\n                "))):(y+="\n                if(xC >= 0 && xC < ".concat(u," && xTexelC").concat(j,"Ready == 0) {\n                  xTexelC").concat(j," = getX(batch, xR, xC, d1);\n                  if (xC + 1 >= ").concat(u,") {\n                    xTexelC").concat(j,".zw = vec2(0.0);\n                  }\n                  xTexelC").concat(j,"Ready = 1;\n                }\n\n                xCOffset = xC + ").concat(p,";\n                if(xCOffset >= 0 && xCOffset < ").concat(u," && xTexelC").concat(j+1,"Ready == 0) {\n                  xTexelC").concat(j+1," = getX(batch, xR, xCOffset, d1);\n                  if (xCOffset + 1 >= ").concat(u,") {\n                    xTexelC").concat(j+1,".zw = vec2(0.);\n                  }\n                  xTexelC").concat(j+1,"Ready = 1;\n                }\n\n                xC").concat(j," = vec4(\n                  xTexelC").concat(j,".xy, xTexelC").concat(j+1,".xy);\n              "),S+1<v&&(y+="\n                  xC".concat(j+1," = vec4(xTexelC").concat(j,".zw, xTexelC").concat(j+1,".zw);\n                "))));j<v&&(y+="\n            wTexel = getW(".concat(x,", ").concat(S,", d1, q);\n            dotProd += xC").concat(j," * vec4(wTexel.xz, wTexel.xz);\n          "),S+1<v&&(y+="\n              wTexel = getW(".concat(x,", ").concat(S+1,", d1, q);\n              dotProd += xC").concat(j+1," * vec4(wTexel.xz, wTexel.xz);\n            ")))}y+="\n        }\n      "}var I="",C="";r&&(I=a?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          ".concat(r,"\n        }"):o?"vec4 activation(vec4 a) {\n          vec4 b = getLeakyreluAlphaAtOutCoords();\n          ".concat(r,"\n        }"):"vec4 activation(vec4 x) {\n          ".concat(r,"\n        }"),C="result = activation(result);");var T=n?"result += getBiasAtOutCoords();":"";n&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),o&&this.variableNames.push("leakyreluAlpha"),this.userCode="\n      ".concat(I,"\n\n      const ivec2 strides = ivec2(").concat(f,", ").concat(p,");\n      const ivec2 pads = ivec2(").concat(l,", ").concat(d,");\n\n      void main() {\n\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / ").concat(s,";\n        int q = d2 - d1 * ").concat(s,";\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.\n        vec4 dotProd = vec4(0.000000000000001);\n\n        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  if (xR < 0 || xR >= ").concat(t.inHeight,") {\n              continue;\n            }\n\n            for (int yC = 0; yC < ").concat(t.outWidth,"; yC++) {\n              int xC = wC + yC * ").concat(r," - ").concat(i,";\n\n              if (xC < 0 || xC >= ").concat(t.inWidth,") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")},Tw=function e(t){Object(Yr.a)(this,e),this.variableNames=["dy","W"],this.outputShape=t.inShape;var n=t.filterHeight,r=t.filterWidth,a=t.strideHeight,i=t.strideWidth,o=n-1-t.padInfo.top,s=r-1-t.padInfo.left,c=t.outChannels/t.inChannels;this.userCode="\n      const ivec2 pads = ivec2(".concat(o,", ").concat(s,");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < ").concat(n,"; wR++) {\n          float dyR = float(dyRCorner + wR) / ").concat(a,".0;\n\n          if (dyR < 0.0 || dyR >= ").concat(t.outHeight,".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = ").concat(n," - 1 - wR;\n\n          for (int wC = 0; wC < ").concat(r,"; wC++) {\n            float dyC = float(dyCCorner + wC) / ").concat(i,".0;\n\n            if (dyC < 0.0 || dyC >= ").concat(t.outWidth,".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = ").concat(r," - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < ").concat(c,"; dm++) {\n              int d2 = d1 * ").concat(c," + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")};var Ew={kernelName:i.P,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.dy,s=r.strides,c=r.dilations,u=r.pad,l=r.dimRoundingMode,d=r.filterShape,f=i.ud.computeConv2DInfo(a.shape,d,s,c,u,l,!0),p=new Cw(f);return n.runWebGLProgram(p,[a,o],"float32")}};var Aw={kernelName:i.Q,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.dy,o=t.filter,s=r.strides,c=r.dilations,u=r.pad,l=r.dimRoundingMode,d=r.inputShape,f=i.ud.computeConv2DInfo(d,o.shape,s,c,u,l,!0),p=new Tw(f);return n.runWebGLProgram(p,[a,o],"float32")}},Rw=function e(t){Object(Yr.a)(this,e),this.variableNames=["X"],this.outputShape=[t,t],this.userCode="\n      void main() {\n          ivec2 coords = getOutputCoords();\n  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_w={kernelName:i.S,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=e.attrs,o=n.x,s=n.filter,c=a.strides,u=a.pad,l=a.dilations,d=i.ud.computeDilation2DInfo(o.shape,s.shape,c,u,"NHWC",l),f=new Dw(d),p=yx({inputs:{x:t=r.runWebGLProgram(f,[o,s],"float32")},backend:r,attrs:{shape:d.outShape}});return r.disposeIntermediateTensorInfo(t),p}};var Mw={kernelName:i.V,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs.equation,a=t,o=i.ud.decodeEinsumEquation(r,a.length),s=o.allDims,c=o.summedDims,u=o.idDims;i.ud.checkEinsumDimSizes(s.length,u,a);for(var l=i.ud.getEinsumComputePath(c,u),d=l.path,f=l.steps,p=f.length,h=null,b=s.length,m=[],v=0;v<p;++v){var g,y=Object(ea.a)(f[v]);try{for(y.s();!(g=y.n()).done;){var O=g.value,x=i.ud.getEinsumPermutation(b,u[O]),k=x.permutationIndices,w=x.expandDims,j=void 0;i.ud.isIdentityPermutation(k)?j=a[O]:(j=Tx({inputs:{x:a[O]},backend:n,attrs:{perm:k}}),m.push(j));for(var S=j.shape.slice(),N=0;N<w.length;++N)S.splice(w[N],0,1);i.wf.arraysEqual(j.shape,S)||(j=yx({inputs:{x:j},backend:n,attrs:{shape:S}}),m.push(j)),null===h?h=j:(h=vx({inputs:{a:j,b:h},backend:n}),m.push(h))}}catch(E){y.e(E)}finally{y.f()}v<p-1&&(d[v]>=0&&(h=Ix({inputs:{x:h},backend:n,attrs:{axis:d[v]-(s.length-b),keepDims:!1}}),m.push(h)),b--)}for(var I=0,C=m;I<C.length;I++){var T=C[I];T!==h&&n.disposeIntermediateTensorInfo(T)}return h}},zw=ux({opSnippet:"return (x >= 0.0) ? x : (exp(x) - 1.0);",packedOpSnippet:"\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n"}),Lw={kernelName:i.W,backendName:"webgl",kernelFunc:zw},Pw={kernelName:i.X,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.dy,a=t.y,o=Object(i.Ud)().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ZO("\n  vec4 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a3)*t + a2)*t + a1)*t*exp(-x*x));\n")}),Vw={kernelName:i.Z,backendName:"webgl",kernelFunc:Uw},Hw="return exp(x);",Gw=ux({opSnippet:Hw,packedOpSnippet:Hw,cpuKernelImpl:Vy}),qw={kernelName:i.ab,backendName:"webgl",kernelFunc:Gw};function Kw(e){var t=e.inputs,n=e.attrs,r=e.backend,a=n.dim,o=t.input,s=o.shape.length,c=o.shape.slice(),u=a;return a<0&&(i.wf.assert(-(s+1)<=a,(function(){return"Axis must be in the interval [".concat(-(s+1),", ").concat(s,"]")})),u=s+a+1),c.splice(u,0,1),yx({inputs:{x:o},backend:r,attrs:{shape:c}})}var Xw={kernelName:i.bb,backendName:"webgl",kernelFunc:Kw},Yw="return exp(x) - 1.0;",$w=ux({opSnippet:Yw,packedOpSnippet:Yw,cpuKernelImpl:Hy}),Qw={kernelName:i.cb,backendName:"webgl",kernelFunc:$w},Zw=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["real","imag"];var a=n[1];this.outputShape=n;var i,o=r?"2.0 * ".concat(Math.PI):"-2.0 * ".concat(Math.PI),s=r?"".concat(a,".0"):"1.0";if("real"===t)i="return real * expR - imag * expI;";else{if("imag"!==t)throw new Error('FFT component must be either "real" or "imag", got '.concat(t,"."));i="return real * expI + imag * expR;"}this.userCode="\n      const float exponentMultiplier = ".concat(o,";\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        ").concat(i,"\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float(").concat(a,");\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < ").concat(a,"; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / ").concat(s,";\n        }\n\n        return result;\n      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getImage(coords[0], coords[1], coordX, coords[3]);\n          } else {\n            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);\n          }\n          setOutput(outputValue);\n        }\n    ")},oj={kernelName:i.fb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.image,a=n,i=new ij(r.shape);return a.runWebGLProgram(i,[r],r.dtype)}},sj="return floor(x);",cj=ux({opSnippet:sj,packedOpSnippet:sj,cpuKernelImpl:Gy}),uj={kernelName:i.gb,backendName:"webgl",kernelFunc:cj},lj=lx({opSnippet:"\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n",packedOpSnippet:"\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int 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== 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    ")},pj=function e(t){Object(Yr.a)(this,e),this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var n=Wg(),r=Object(o.a)(t,2),a=r[0],i=r[1];this.outputShape=t,this.userCode="\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n\n        vec4 result = vec4(0.);\n\n        for(int row=0; row<=1; row++) {\n          for(int col=0; col<=1; col++) {\n            texC = coords[1] + row;\n            depth = coords[2] + col;\n\n            vec2 uv = (vec2(texC, texR) + halfCR) /\n                       vec2(".concat(i,".0, ").concat(a,".0);\n            vec4 values = ").concat(n.texture2D,"(A, uv);\n            float value;\n            if (depth == 0) {\n              value = values.r;\n            } else if (depth == 1) {\n              value = values.g;\n            } else if (depth == 2) {\n              value = values.b;\n            } else if (depth == 3) {\n              value = values.a;\n            }\n\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\n          }\n        }\n\n        ").concat(n.output," = result;\n      }\n    ")},hj={kernelName:i.ib,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.pixels,s=r.numChannels,c="undefined"!==typeof HTMLVideoElement&&a instanceof HTMLVideoElement,u="undefined"!==typeof HTMLImageElement&&a instanceof HTMLImageElement,l=c?[a.videoWidth,a.videoHeight]:[a.width,a.height],d=Object(o.a)(l,2),f=d[0],p=d[1],h=[p,f],b=[p,f,s];(u||c)&&(null==rj&&(rj=document.createElement("canvas").getContext("2d")),rj.canvas.width=f,rj.canvas.height=p,rj.drawImage(a,0,0,f,p),a=rj.canvas);var m=n.makeTensorInfo(h,"int32");n.texData.get(m.dataId).usage=ag.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(m.dataId),a);var v=Object(i.Ud)().getBool("WEBGL_PACK")?new pj(b):new fj(b),g=n.runWebGLProgram(v,[m],"int32");return n.disposeData(m.dataId),g}};var bj={kernelName:i.kb,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=e.attrs,o=n.x,s=n.filter,c=n.bias,u=n.preluActivationWeights,l=a.strides,d=a.pad,f=a.dataFormat,p=a.dilations,h=a.dimRoundingMode,b=a.activation,m=a.leakyreluAlpha,v=i.ud.convertConv2DDataFormat(f),g=i.ud.computeConv2DInfo(o.shape,s.shape,l,p,d,h,!1,v),y=[];if(1!==g.filterHeight||1!==g.filterWidth||1!==g.dilationHeight||1!==g.dilationWidth||1!==g.strideHeight||1!==g.strideWidth||"SAME"!==g.padInfo.type&&"VALID"!==g.padInfo.type)if(Object(i.Ud)().getBool("WEBGL_CONV_IM2COL")&&1===o.shape[0])t=tw({x:o,filter:s,convInfo:g,backend:r,bias:c,activation:b,preluActivationWeights:u,leakyreluAlpha:m});else{var O=null!=c,x=null!=u,k="leakyrelu"===b,w=b?dx(b,!1):null,j=new Qk(g,O,w,x,k),S=[o,s];if(c&&S.push(c),u&&S.push(u),k){var N=r.makeTensorInfo([],"float32",i.wf.createScalarValue(m,"float32"));S.push(N),y.push(N)}t=r.runWebGLProgram(j,S,"float32")}else t=ew({x:o,filter:s,convInfo:g,backend:r,bias:c,activation:b,preluActivationWeights:u,leakyreluAlpha:m});var I=yx({inputs:{x:t},backend:r,attrs:{shape:g.outShape}});return y.push(t),y.forEach((function(e){return r.disposeIntermediateTensorInfo(e)})),I}};var mj={kernelName:i.lb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.filter,s=t.bias,c=t.preluActivationWeights,u=r.strides,l=r.pad,d=r.dilations,f=r.dimRoundingMode,p=r.activation,h=r.leakyreluAlpha,b=[],m=d;null==m&&(m=[1,1]),i.wf.assert(i.ud.eitherStridesOrDilationsAreOne(u,m),(function(){return"Error in depthwiseConv2d: Either strides or dilations must be "+"1. 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j++) {\n            int index = round(getIndices(coords[0], j));\n            flattenIndex += index * ").concat(o,";\n          }\n          setOutput(getX(flattenIndex, coords[1]));\n        }\n      ")};var gj={kernelName:i.mb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.params,a=t.indices,s=a.shape,c=s[s.length-1],u=i.wf.sizeFromShape(r.shape),l=i.ud.prepareAndValidate(r,a),d=Object(o.a)(l,4),f=d[0],p=d[1],h=d[2],b=d[3],m=yx({inputs:{x:a},backend:n,attrs:{shape:[p,c]}}),v=yx({inputs:{x:r},backend:n,attrs:{shape:[i.wf.sizeFromShape(r.shape)/h,h]}});if(n.shouldExecuteOnCPU([r,a])||"string"===r.dtype){var g=n.readSync(a.dataId),y=n.bufferSync(r),O=qy(g,y,r.dtype,p,c,h,b,r.shape,u);return n.makeTensorInfo(f,r.dtype,O.values)}var x=new vj(c,b,[p,h]),k=n.runWebGLProgram(x,[v,m],v.dtype),w=yx({inputs:{x:k},backend:n,attrs:{shape:f}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(v),n.disposeIntermediateTensorInfo(k),w}},yj=function e(t,n){Object(Yr.a)(this,e),this.variableNames=["A","indices"],this.outputShape=n,this.rank=n.length;var r=Cy(this.rank),a=function(e,t){for(var n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[],a=0;a<e.length;a++)2===a?r.push("int(getIndices(resRC.x, resRC.z))"):r.push("".concat(n[a]));return r.join()}(t);this.userCode="\n      void main() {\n        ".concat(r," resRC = getOutputCoords();\n        setOutput(getA(").concat(a,"));\n      }\n    ")};function Oj(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=t.indices,s=r.axis,c=r.batchDims,u=i.wf.parseAxisParam(s,a.shape)[0],l=i.ud.segment_util.collectGatherOpShapeInfo(a,o,u,c),d=i.wf.sizeFromShape(o.shape),f=[],p=yx({inputs:{x:a},backend:n,attrs:{shape:[l.batchSize,l.outerSize,l.dimSize,l.sliceSize]}}),h=yx({inputs:{x:o},backend:n,attrs:{shape:[l.batchSize,d/l.batchSize]}});f.push(p),f.push(h);var b=[l.batchSize,l.outerSize,d/l.batchSize,l.sliceSize];if(n.shouldExecuteOnCPU([a,o])||"string"===a.dtype){var m=n.bufferSync(h),v=n.bufferSync(p),g=Ky(v,m,b);return f.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),n.makeTensorInfo(l.outputShape,g.dtype,g.values)}var y=new yj(p.shape,b),O=n.runWebGLProgram(y,[p,h],p.dtype);f.push(O);var x=yx({inputs:{x:O},backend:n,attrs:{shape:l.outputShape}});return f.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),x}var xj={kernelName:i.nb,backendName:"webgl",kernelFunc:Oj},kj=lx({opSnippet:"return float(a > b);",packedOpSnippet:"\n  return vec4(greaterThan(a, b));\n",cpuKernelImpl:Xy,dtype:"bool"}),wj={kernelName:i.ob,backendName:"webgl",kernelFunc:kj},jj=lx({opSnippet:"return float(a >= b);",packedOpSnippet:"\n  return vec4(greaterThanEqual(a, b));\n",dtype:"bool",cpuKernelImpl:Yy}),Sj={kernelName:i.pb,backendName:"webgl",kernelFunc:jj};var Nj={kernelName:i.qb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend;return Jw(t.input,!0,n)}},Ij=ux({opSnippet:"return float(!isnan(x) && !isinf(x));",dtype:"bool"}),Cj={kernelName:i.tb,backendName:"webgl",kernelFunc:Ij},Tj=ux({opSnippet:"return float(isinf(x));",dtype:"bool"}),Ej={kernelName:i.ub,backendName:"webgl",kernelFunc:Tj},Aj=ux({opSnippet:"return float(isnan(x));",dtype:"bool"}),Rj={kernelName:i.vb,backendName:"webgl",kernelFunc:Aj},Fj=lx({opSnippet:"return float(a < b);",packedOpSnippet:"\n  return vec4(lessThan(a, b));\n",cpuKernelImpl:$y,dtype:"bool"}),Dj={kernelName:i.Ab,backendName:"webgl",kernelFunc:Fj},_j=lx({opSnippet:"return float(a <= b);",packedOpSnippet:"\n  return vec4(lessThanEqual(a, b));\n",cpuKernelImpl:Qy,dtype:"bool"}),Mj={kernelName:i.Bb,backendName:"webgl",kernelFunc:_j};var zj={kernelName:i.Cb,backendName:"webgl",kernelFunc:function(e){var t=e.backend,n=e.attrs,r=n.start,a=n.stop,i=n.num,o=Zy(r,a,i);return t.makeTensorInfo([o.length],"float32",o)}},Lj=ux({opSnippet:"if (x < 0.0) return NAN;\n  return log(x);",packedOpSnippet:"\n  vec4 result = log(x);\n  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\n\n  return result;\n",cpuKernelImpl:Jy}),Pj={kernelName:i.Db,backendName:"webgl",kernelFunc:Lj},Bj=ux({opSnippet:"return log(1.0 + x);"}),Wj={kernelName:i.Eb,backendName:"webgl",kernelFunc:Bj},Uj=lx({opSnippet:"return float(a >= 1.0 && b >= 1.0);",packedOpSnippet:"\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n",dtype:"bool"}),Vj={kernelName:i.Fb,backendName:"webgl",kernelFunc:Uj},Hj=ux({opSnippet:"return float(!(x >= 1.0));"}),Gj={kernelName:i.Gb,backendName:"webgl",kernelFunc:Hj},qj=lx({opSnippet:"return float(a >= 1.0 || b >= 1.0);",packedOpSnippet:"\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n",dtype:"bool"}),Kj={kernelName:i.Hb,backendName:"webgl",kernelFunc:qj},Xj=function e(t,n,r,a,i){Object(Yr.a)(this,e),this.variableNames=["x"],this.outputShape=[];var o,s=n,c=t[3]-1;this.outputShape=t;var u="float(".concat(r,") + float(").concat(a,") * sum");o=.5===i?"inversesqrt(".concat(u,")"):1===i?"1.0/(".concat(u,")"):"exp(log(".concat(u,") * float(-").concat(i,"));"),this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -".concat(s,"; j <= ").concat(s,"; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  ").concat(c,") {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * ").concat(o,";\n        setOutput(val);\n      }\n    ")},Yj=function e(t,n,r,a,i){Object(Yr.a)(this,e),this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;var o,s=n,c=t[3]-1;this.outputShape=t;var u="float(".concat(r,") + float(").concat(a,") * sum");o=.5===i?"inversesqrt(".concat(u,")"):1===i?"1.0/(".concat(u,")"):"exp(log(".concat(u,") * float(-").concat(i,"));"),this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < ".concat(this.outputShape[3],";\n        bool hasNextRow = c < ").concat(this.outputShape[2],";\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - ").concat(s,";\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - ").concat(s,"; j <= ").concat(s,"; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(").concat(c,"));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * ").concat(o,";\n        setOutput(result);\n      }\n    ")},$j={kernelName:i.xb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.depthRadius,s=r.bias,c=r.alpha,u=r.beta,l=Object(i.Ud)().getBool("WEBGL_PACK_NORMALIZATION")?new Yj(a.shape,o,s,c,u):new Xj(a.shape,o,s,c,u);return n.runWebGLProgram(l,[a],a.dtype)}},Qj=function e(t,n,r,a,i){Object(Yr.a)(this,e),this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=n,this.bias=r,this.alpha=a,this.beta=i,this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < ".concat(this.depth,"; ++d) {\n          int depthBegin = int(max(0.0, float(d - ").concat(n,")));\n          int depthEnd = int(min(float(").concat(this.depth,"),\n              float(d + ").concat(n," + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = ").concat(this.depth,";\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float(").concat(a,") * norm + float(").concat(r,");\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float(").concat(a,")\n                * float(").concat(i,")\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * ").concat(i,");\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    ")},Zj={kernelName:i.yb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,i=t.y,o=t.dy,s=r.depthRadius,c=r.bias,u=r.alpha,l=r.beta,d=new Qj(a.shape,s,c,u,l);return n.runWebGLProgram(d,[a,i,o],a.dtype)}};function Jj(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.reductionIndices,c=r.keepDims,u=a.shape.length,l=i.wf.parseAxisParam(s,a.shape),d=l,f=i.ud.getAxesPermutation(d,u),p=null!=f,h=n.shouldExecuteOnCPU([a]),b=a;if(p){if(h){for(var m=n.texData.get(b.dataId).values,v=new Array(u),g=0;g<v.length;g++)v[g]=a.shape[f[g]];var y=xO(m,a.shape,a.dtype,f,v);b=n.makeTensorInfo(v,a.dtype),n.texData.get(b.dataId).values=y}else b=Nx(a,f,n);d=i.ud.getInnerMostAxes(d.length,u)}i.ud.assertAxesAreInnerMostDims("max",d,u);var O,x=i.ud.computeOutAndReduceShapes(b.shape,d),k=Object(o.a)(x,2),w=k[0],j=k[1],S=w;if(c&&(S=i.ud.expandShapeToKeepDim(w,l)),h){var N=n.texData.get(b.dataId).values,I=eO(N,i.wf.sizeFromShape(j),S,a.dtype);O=n.makeTensorInfo(S,a.dtype),n.texData.get(O.dataId).values=I}else O=function(e,t,n,r){var a=i.wf.sizeFromShape(t),o=yx({inputs:{x:e},attrs:{shape:[i.wf.sizeFromShape(e.shape)/a,a]},backend:r}),s=wx(o,e.dtype,"max",r),c=yx({inputs:{x:s},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(s),c}(b,j,S,n);return p&&n.disposeIntermediateTensorInfo(b),O}var eS={kernelName:i.Ib,backendName:"webgl",kernelFunc:Jj},tS=lx({opSnippet:"\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return max(a, b);\n",packedOpSnippet:"\n  vec4 result = vec4(max(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",cpuKernelImpl:tO}),nS={kernelName:i.Ob,backendName:"webgl",kernelFunc:tS};var rS={kernelName:i.Jb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x;Pg(a,"maxPool");var o=r.filterSize,s=r.strides,c=r.pad,u=r.dimRoundingMode;i.wf.assert(i.ud.eitherStridesOrDilationsAreOne(s,1),(function(){return"Error in maxPool: Either strides or dilations must be 1. "+"Got strides ".concat(s," and dilations '").concat(1,"'")}));var l=i.ud.computePool2DInfo(a.shape,o,s,1,c,u);if(1===l.filterWidth&&1===l.filterHeight&&i.wf.arraysEqual(l.inShape,l.outShape))return JO({inputs:{x:a},backend:n});var d=new lk(l,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}};var aS={kernelName:i.Kb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.filterSize,s=r.strides,c=r.pad,u=r.dataFormat,l=r.dimRoundingMode,d=i.ud.computePool3DInfo(a.shape,o,s,[1,1,1],c,l,u),f=new dk(d,"max",!1);return n.runWebGLProgram(f,[a],a.dtype)}},iS=function e(t){Object(Yr.a)(this,e),this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var n=t.strideHeight,r=t.strideWidth,a=t.dilationHeight,i=t.effectiveFilterHeight,o=t.effectiveFilterWidth,s=i-1-t.padInfo.top,c=o-1-t.padInfo.left,u=i*o-1;this.userCode="\n      const ivec2 pads = ivec2(".concat(s,", ").concat(c,");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ").concat(i,";\n          wR += ").concat(a,") {\n          float dyR = float(dyRCorner + wR) / ").concat(n,".0;\n\n          if (dyR < 0.0 || dyR >= ").concat(t.outHeight,".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < ").concat(o,"; wC++) {\n            float dyC = float(dyCCorner + wC) / ").concat(r,".0;\n\n            if (dyC < 0.0 || dyC >= ").concat(t.outWidth,".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = ").concat(u," - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * ").concat(o," + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    ")},oS=function e(t){Object(Yr.a)(this,e),this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var n=t.strideDepth,r=t.strideHeight,a=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,s=t.dilationWidth,c=t.effectiveFilterDepth,u=t.effectiveFilterHeight,l=t.effectiveFilterWidth,d=c-1-t.padInfo.front,f=u-1-t.padInfo.top,p=l-1-t.padInfo.left,h=c*u*l-1;this.userCode="\n      const ivec3 pads = ivec3(".concat(d,", ").concat(f,", ").concat(p,");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < ").concat(c,";\n           wD += ").concat(i,") {\n          float dyD = float(dyDCorner + wD) / ").concat(n,".0;\n\n          if (dyD < 0.0 || dyD >= ").concat(t.outDepth,".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < ").concat(u,";\n              wR += ").concat(o,") {\n            float dyR = float(dyRCorner + wR) / ").concat(r,".0;\n\n            if (dyR < 0.0 || dyR >= ").concat(t.outHeight,".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < ").concat(l,";\n                wC += ").concat(s,") {\n              float dyC = float(dyCCorner + wC) / ").concat(a,".0;\n\n              if (dyC < 0.0 || dyC >= ").concat(t.outWidth,".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = ").concat(h," -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * ").concat(u," * ").concat(l," +\n                  wR * ").concat(l," + wC;\n              float mask = float(maxPosValue == curPosValue ? 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"+"Got strides ".concat(c," and dilations '").concat(f,"'")}));var p=i.ud.computePool2DInfo(a.shape,s,c,f,u),h=function(e,t,n,r){var a=new lk(n,"max",!1),i=r.runWebGLProgram(a,[e],"float32");return a=new lk(n,"max",!0,!0,t),[i,r.runWebGLProgram(a,[e],"float32")]}(a,l,p,d),b=Object(o.a)(h,2);return[b[0],b[1]]}};var lS={kernelName:i.Pb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.attrs,r=e.backend,a=t.x,s=n.keepDims,c=n.axis,u=r,l=a.shape.length,d=i.wf.parseAxisParam(c,a.shape),f=d,p=i.ud.getAxesPermutation(f,l),h=null!=p,b=u.shouldExecuteOnCPU([a]),m=[],v=a;if(h){if(b){for(var g=u.texData.get(v.dataId).values,y=new Array(l),O=0;O<y.length;O++)y[O]=a.shape[p[O]];var x=xO(g,a.shape,a.dtype,p,y);v=u.makeTensorInfo(y,a.dtype),u.texData.get(v.dataId).values=x}else v=Nx(a,p,u);m.push(v),f=i.ud.getInnerMostAxes(f.length,l)}i.ud.assertAxesAreInnerMostDims("sum",f,l);var k=i.ud.computeOutAndReduceShapes(v.shape,f),w=Object(o.a)(k,2),j=w[0],S=w[1],N=j;s&&(N=i.ud.expandShapeToKeepDim(j,d));for(var I=function(e,t,n,r){var a=i.wf.sizeFromShape(t),o=yx({inputs:{x:e},attrs:{shape:[i.wf.sizeFromShape(e.shape)/a,a]},backend:r}),s=wx(o,"float32","mean",r),c=yx({inputs:{x:s},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(s),c}(v,S,N,u),C=0,T=m;C<T.length;C++){var E=T[C];u.disposeIntermediateTensorInfo(E)}return I}};var dS={kernelName:i.Qb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.axis,c=r.keepDims,u=a.shape.length,l=i.wf.parseAxisParam(s,a.shape),d=l,f=i.ud.getAxesPermutation(d,u),p=a;null!=f&&(p=Tx({inputs:{x:a},backend:n,attrs:{perm:f}}),d=i.ud.getInnerMostAxes(d.length,a.shape.length)),i.ud.assertAxesAreInnerMostDims("min",d,u);var h,b=i.ud.computeOutAndReduceShapes(p.shape,d),m=Object(o.a)(b,2),v=m[0],g=m[1],y=yx({inputs:{x:p},backend:n,attrs:{shape:[-1,i.wf.sizeFromShape(g)]}}),O=wx(y,y.dtype,"min",n);return h=yx(c?{inputs:{x:O},backend:n,attrs:{shape:i.ud.expandShapeToKeepDim(v,l)}}:{inputs:{x:O},backend:n,attrs:{shape:v}}),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(O),null!=f&&n.disposeIntermediateTensorInfo(p),h}},fS=lx({opSnippet:"\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return min(a, b);\n",packedOpSnippet:"\n  vec4 result = vec4(min(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",cpuKernelImpl:nO}),pS={kernelName:i.Rb,backendName:"webgl",kernelFunc:fS},hS=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["x"],this.outputShape=n.map((function(e,n){return e[0]+t[n]+e[1]}));var a=t.length,i=Cy(a),o=n.map((function(e){return e[0]})).join(","),s=n.map((function(e,n){return e[0]+t[n]})).join(","),c=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a),u="reflect"===r?0:1;this.userCode=1!==a?"\n      ".concat(i," start = ").concat(i,"(").concat(o,");\n      ").concat(i," end = ").concat(i,"(").concat(s,");\n\n      void main() {\n        ").concat(i," outC = getOutputCoords();\n        for (int i = 0; i < ").concat(a,"; i++) {\n          if (outC[i] < start[i]) {\n            outC[i] = start[i] * 2 - outC[i] - ").concat(u,";\n          } else if(outC[i] >= end[i]) {\n            outC[i] = (end[i] - 1) * 2 - outC[i] + ").concat(u,";\n          }\n        }\n        ").concat(i," coords = outC - start;\n        setOutput(getX(").concat(c,"));\n      }\n    "):"\n        int start = ".concat(o,";\n        int end = ").concat(s,";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start) {\n            outC = start * 2 - outC - ").concat(u,";\n          } else if(outC >= end) {\n            outC = (end - 1) * 2 - outC + ").concat(u,";\n          }\n          setOutput(getX(outC - start));\n        }\n      ")},bS=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n.map((function(e,n){return e[0]+t[n]+e[1]}));var a=t.length,i=Cy(a),o=n.map((function(e){return e[0]})).join(","),s=n.map((function(e,n){return e[0]+t[n]})).join(","),c=jO("rc",a),u=jO("source",a),l="".concat(c[a-1]," < ").concat(this.outputShape[a-1]),d=1===a?"source":"vec2(".concat(u.slice(-2).join(),")"),f="reflect"===r?0:1,p="";if(1===a){var h="\n        ".concat(i," source = rc;\n        if (source < start) {\n          source = start * 2 - source - ").concat(f,";\n        } else if (source >= end) {\n          source = (end - 1) * 2 - source + ").concat(f,";\n        }\n        source -= start;\n      ");p="\n        ".concat(i," rc = outputLoc;\n        ").concat(h,"\n        result[0] = getChannel(getX(").concat(u.join(),"), ").concat(d,");\n        ").concat(c[a-1]," += 1;\n        if(").concat(l,") {\n          ").concat(h,"\n          result[1] = getChannel(getX(").concat(u.join(),"), ").concat(d,");\n        }\n      ")}else{var b="\n        ".concat(i," source = rc;\n        ").concat(i," lt = ").concat(i,"(lessThan(source, start));\n        ").concat(i," gte = ").concat(i,"(greaterThanEqual(source, end));\n        ").concat(i," orig = 1 - (lt + gte);\n        source = orig * source +\n                lt * (start * 2 - source - ").concat(f,") +\n                gte * ((end - 1) * 2 - source + ").concat(f,");\n        source -= start;\n      ");p="\n        ".concat(i," rc = outputLoc;\n        ").concat(b,"\n        result[0] = getChannel(getX(").concat(u.join(),"), ").concat(d,");\n        ").concat(c[a-1]," += 1;\n        if(").concat(l,") {\n          ").concat(b,"\n          result[1] = getChannel(getX(").concat(u.join(),"), ").concat(d,");\n        }\n        rc = outputLoc;\n        ").concat(c[a-2]," += 1;\n        if(").concat(c[a-2]," < ").concat(this.outputShape[a-2],") {\n          ").concat(b,"\n          result[2] = getChannel(getX(").concat(u.join(),"), ").concat(d,");\n          ").concat(c[a-1]," += 1;\n          if(").concat(l,") {\n            ").concat(b,"\n            result[3] = getChannel(getX(").concat(u.join(),"), ").concat(d,");\n          }\n        }\n      ")}this.userCode="\n      const ".concat(i," start = ").concat(i,"(").concat(o,");\n      const ").concat(i," end = ").concat(i,"(").concat(s,");\n\n      void main() {\n        ").concat(i," outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        ").concat(p,"\n        setOutput(result);\n      }\n    ")},mS={kernelName:i.Sb,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.paddings,s=r.mode,c=Object(i.Ud)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new bS(a.shape,o,s):new hS(a.shape,o,s);return n.runWebGLProgram(c,[a],a.dtype)}},vS=lx({opSnippet:"if (b == 0.0) return NAN;\n  return mod(a, b);",packedOpSnippet:"\n  vec4 result = mod(a, b);\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n"}),gS={kernelName:i.Tb,backendName:"webgl",kernelFunc:vS},yS=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[t,r],this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < ".concat(n-1,"; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float(").concat(n-1,"));\n      }\n    ")},OS=lx({opSnippet:"\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;",packedOpSnippet:"\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n",checkOutOfBounds:!0}),xS={kernelName:i.lc,backendName:"webgl",kernelFunc:OS},kS="return a - b;",wS=lx({opSnippet:kS,packedOpSnippet:kS,supportsComplex:!0,cpuKernelImpl:gO}),jS={kernelName:i.Xc,backendName:"webgl",kernelFunc:wS};function SS(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.logits,o=r.dim,s=i.wf.parseAxisParam([o],a.shape),c=Jj({inputs:{x:a},backend:n,attrs:{reductionIndices:s,keepDims:!1}}),u=i.ud.expandShapeToKeepDim(c.shape,s),l=yx({inputs:{x:c},backend:n,attrs:{shape:u}}),d=wS({inputs:{a:a,b:l},backend:n}),f=Gw({inputs:{x:d},backend:n}),p=Ix({inputs:{x:f},backend:n,attrs:{axis:s,keepDims:!1}}),h=yx({inputs:{x:p},backend:n,attrs:{shape:u}}),b=OS({inputs:{a:f,b:h},backend:n});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(l),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(h),b}var NS={kernelName:i.Gc,backendName:"webgl",kernelFunc:SS};var IS={kernelName:i.Ub,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.logits,i=r.numSamples,o=r.seed,s=r.normalized,c=s?a:SS({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),u=c.shape[0],l=c.shape[1],d=new yS(u,l,i),f=[[o]],p=n.runWebGLProgram(d,[c],"int32",f);return s||n.disposeIntermediateTensorInfo(c),p}},CS="return -x;";var TS={kernelName:i.Wb,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=n.x;if(r.shouldExecuteOnCPU([a])){var s=r.texData.get(a.dataId),c=aO(s.values,a.shape,a.dtype),u=Object(o.a)(c,2),l=u[0],d=u[1];return r.makeTensorInfo(d,a.dtype,l)}return t=Object(i.Ud)().getBool("WEBGL_PACK_UNARY_OPERATIONS")?new GO(a.shape,CS):new AO(a.shape,CS),r.runWebGLProgram(t,[a],a.dtype)}},ES=i.ie.nonMaxSuppressionV3Impl;var AS={kernelName:i.Xb,backendName:"webgl",kernelFunc:function(e){i.ud.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");var t=e.inputs,n=e.backend,r=e.attrs,a=t.boxes,o=t.scores,s=r.maxOutputSize,c=r.iouThreshold,u=r.scoreThreshold,l=n.readSync(a.dataId),d=n.readSync(o.dataId),f=ES(l,d,s,c,u).selectedIndices;return n.makeTensorInfo([f.length],"int32",new Int32Array(f))}},RS=i.ie.nonMaxSuppressionV4Impl;var FS={kernelName:i.Yb,backendName:"webgl",kernelFunc:function(e){i.ud.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");var t=e.inputs,n=e.backend,r=e.attrs,a=t.boxes,o=t.scores,s=r.maxOutputSize,c=r.iouThreshold,u=r.scoreThreshold,l=r.padToMaxOutputSize,d=n.readSync(a.dataId),f=n.readSync(o.dataId),p=RS(d,f,s,c,u,l),h=p.selectedIndices,b=p.validOutputs;return[n.makeTensorInfo([h.length],"int32",new Int32Array(h)),n.makeTensorInfo([],"int32",new Int32Array([b]))]}},DS=i.ie.nonMaxSuppressionV5Impl;var _S={kernelName:i.Zb,backendName:"webgl",kernelFunc:function(e){i.ud.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");var t=e.inputs,n=e.backend,r=e.attrs,a=t.boxes,o=t.scores,s=r.maxOutputSize,c=r.iouThreshold,u=r.scoreThreshold,l=r.softNmsSigma,d=n.readSync(a.dataId),f=n.readSync(o.dataId),p=DS(d,f,s,c,u,l),h=p.selectedIndices,b=p.selectedScores;return[n.makeTensorInfo([h.length],"int32",new Int32Array(h)),n.makeTensorInfo([b.length],"float32",new Float32Array(b))]}},MS=function e(t,n,r,a){Object(Yr.a)(this,e),this.variableNames=["indices"],this.outputShape=[t,n],this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float(".concat(a,"), float(").concat(r,"),\n                      float(index == coords.y)));\n      }\n    ")},zS={kernelName:i.bc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.indices,o=r.depth,s=r.onValue,c=r.offValue,u=i.wf.sizeFromShape(a.shape),l=new MS(u,o,s,c),d=yx({inputs:{x:a},backend:n,attrs:{shape:[u]}}),f=n.runWebGLProgram(l,[d],a.dtype);n.disposeIntermediateTensorInfo(d);var p=yx({inputs:{x:f},backend:n,attrs:{shape:[].concat(Object(Vn.a)(a.shape),[o])}});return n.disposeIntermediateTensorInfo(f),p}};function LS(e){var t=e.inputs,n=e.backend,r=t.x;if("complex64"===r.dtype){var a=Ak({inputs:{input:r},backend:n}),i=LS({inputs:{x:a},backend:n}),o=qk({inputs:{input:r},backend:n}),s=LS({inputs:{x:o},backend:n}),c=tx({inputs:{real:i,imag:s},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(s),c}return nj({attrs:{shape:r.shape,dtype:r.dtype,value:"string"===r.dtype?"":0},backend:n})}var PS={kernelName:i.kd,backendName:"webgl",kernelFunc:LS};var BS={kernelName:i.cc,backendName:"webgl",kernelFunc:function e(t){var n=t.inputs,r=t.backend,a=n.x;if("string"===a.dtype)throw new Error("onesLike is not supported under string dtype");if("complex64"===a.dtype){var i=Ak({inputs:{input:a},backend:r}),o=e({inputs:{x:i},backend:r}),s=qk({inputs:{input:a},backend:r}),c=LS({inputs:{x:s},backend:r}),u=tx({inputs:{real:o,imag:c},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(s),r.disposeIntermediateTensorInfo(c),u}return nj({attrs:{shape:a.shape,dtype:a.dtype,value:1},backend:r})}};var WS={kernelName:i.ec,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs.axis;if(1===t.length)return Kw({inputs:{input:t[0]},backend:n,attrs:{dim:r}});var a=t[0].shape,o=t[0].dtype;t.forEach((function(e){i.wf.assertShapesMatch(a,e.shape,"All tensors passed to stack must have matching shapes"),i.wf.assert(o===e.dtype,(function(){return"All tensors passed to stack must have matching dtypes"}))}));var s=[],c=Yk({inputs:t.map((function(e){var t=Kw({inputs:{input:e},backend:n,attrs:{dim:r}});return s.push(t),t})),backend:n,attrs:{axis:r}});return s.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),c}},US=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=n.map((function(e,n){return e[0]+t[n]+e[1]}));var a=t.length,i=Cy(a),o=n.map((function(e){return e[0]})).join(","),s=n.map((function(e,n){return e[0]+t[n]})).join(","),c=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a);this.userCode=1!==a?"\n      ".concat(i," start = ").concat(i,"(").concat(o,");\n      ").concat(i," end = ").concat(i,"(").concat(s,");\n\n      void main() {\n        ").concat(i," outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(value);\n        } else {\n          ").concat(i," coords = outC - start;\n          setOutput(getX(").concat(c,"));\n        }\n      }\n    "):"\n        int start = ".concat(o,";\n        int end = ").concat(s,";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(value);\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      ")},VS=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=n.map((function(e,n){return e[0]+t[n]+e[1]}));for(var a=t.length,i=Cy(a),o=n.map((function(e){return e[0]})).join(","),s=n.map((function(e,n){return e[0]+t[n]})).join(","),c=jO("rc",a),u=jO("source",a),l="".concat(c[a-1]," < ").concat(this.outputShape[a-1]),d=1===a?"source":"vec2(".concat(u.slice(-2).join(),")"),f=["".concat(i," rc = outputLoc;"),"".concat(c[a-1]," += 1;\n       if(").concat(l,") {\n      "),1===a?"":"}\n       rc = outputLoc;\n       ".concat(c[a-2]," += 1;\n       if(").concat(c[a-2]," < ").concat(this.outputShape[a-2],") {"),1===a?"":"  ".concat(c[a-1]," += 1;\n         if(").concat(l,") {")],p=1===a?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",h="",b=0,m=1===a?2:4;b<m;b++)h+="\n        ".concat(f[b],"\n        if (").concat(p,") {\n          result[").concat(b,"] = float(value);\n        } else {\n          ").concat(i," source = rc - start;\n          result[").concat(b,"] = getChannel(getX(").concat(u.join(),"), ").concat(d,");\n        }\n      ");h+=1===a?"} ":"}}",this.userCode="\n      const ".concat(i," start = ").concat(i,"(").concat(o,");\n      const ").concat(i," end = ").concat(i,"(").concat(s,");\n\n      void main() {\n        ").concat(i," outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        ").concat(h,"\n        setOutput(result);\n      }\n    ")},HS=function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.paddings,s=r.constantValue,c=Object(i.Ud)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new VS(a.shape,o,s):new US(a.shape,o,s),u=[[s]];return n.runWebGLProgram(c,[a],a.dtype,u)},GS={kernelName:i.fc,backendName:"webgl",kernelFunc:HS},qS=lx({opSnippet:"\n  if(a < 0.0 && floor(b) < b){\n    return NAN;\n  }\n  if (b == 0.0) {\n    return 1.0;\n  }\n  return (round(mod(b, 2.0)) != 1) ?\n      pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",packedOpSnippet:"\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n"}),KS={kernelName:i.gc,backendName:"webgl",kernelFunc:qS};var XS={kernelName:i.ic,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=e.attrs,s=n.x,c=a.axis,u=a.keepDims,l=s.shape.length,d=[],f=i.wf.parseAxisParam(c,s.shape),p=f,h=i.ud.getAxesPermutation(p,l),b=s;if(null!=h&&(b=Tx({inputs:{x:s},backend:r,attrs:{perm:h}}),p=i.ud.getInnerMostAxes(p.length,l),d.push(b)),i.ud.assertAxesAreInnerMostDims("prod",p,l),r.shouldExecuteOnCPU([b])){var m=r.texData.get(b.dataId).values,v=oO(b.shape,b.dtype,m,p),g=v.outVals,y=v.outShape,O=v.outDtype;t=r.makeTensorInfo(y,O,g)}else{var x=i.ud.computeOutAndReduceShapes(b.shape,p),k=Object(o.a)(x,2),w=k[0],j=k[1],S=i.wf.sizeFromShape(j),N=yx({inputs:{x:b},backend:r,attrs:{shape:[-1,S]}}),I=wx(N,Object(i.jf)(s.dtype),"prod",r);t=yx({inputs:{x:I},backend:r,attrs:{shape:w}}),d.push(N),d.push(I)}if(u){d.push(t);var C=i.ud.expandShapeToKeepDim(t.shape,f);t=yx({inputs:{x:t},backend:r,attrs:{shape:C}})}return d.forEach((function(e){return r.disposeIntermediateTensorInfo(e)})),t}},YS=function(e){var t=e.backend,n=e.attrs,r=n.start,a=n.stop,i=n.step,o=n.dtype,s=sO(r,a,i,o);return t.makeTensorInfo([s.length],o,s)},$S={kernelName:i.jc,backendName:"webgl",kernelFunc:YS},QS=ux({opSnippet:"return 1.0 / x;"}),ZS={kernelName:i.mc,backendName:"webgl",kernelFunc:QS},JS=ux({opSnippet:"if (isnan(x)) return x;\n  return (x < 0.0) ? 0.0 : x;\n",packedOpSnippet:"\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n"}),eN={kernelName:i.nc,backendName:"webgl",kernelFunc:JS},tN=ux({opSnippet:"if (isnan(x)) return x;\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n",packedOpSnippet:"\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n"}),nN={kernelName:i.oc,backendName:"webgl",kernelFunc:tN},rN=function e(t,n,r,a,i){Object(Yr.a)(this,e),this.variableNames=["A"],this.outputShape=[];var s=Object(o.a)(t,4),c=s[0],u=s[1],l=s[2],d=s[3];this.outputShape=[c,n,r,d];var f,p=[a&&n>1?u-1:u,a&&r>1?l-1:l],h=[a&&n>1?n-1:n,a&&r>1?r-1:r];f=i?"(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":"vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          ".concat(p[0]/h[0],",\n          ").concat(p[1]/h[1],");\n      const vec2 inputShapeRC = vec2(").concat(u,".0, ").concat(l,".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = ").concat(f,";\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    ")},aN=function e(t,n,r,a,i){Object(Yr.a)(this,e),this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var s=Object(o.a)(t,4),c=s[0],u=s[1],l=s[2],d=s[3];this.outputShape=[c,n,r,d];var f,p=[a&&n>1?u-1:u,a&&r>1?l-1:l],h=[a&&n>1?n-1:n,a&&r>1?r-1:r];f=i?"(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":"vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode="\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          ".concat(p[0]/h[0],",\n          ").concat(p[1]/h[1],",\n          ").concat(p[1]/h[1],");\n      const vec3 inputShapeRC = vec3(").concat(u,".0, ").concat(l,".0,\n                                     ").concat(l,".0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = ").concat(f,";\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < ").concat(d-1,";\n        bool hasNextRow = coords.z < ").concat(r-1,";\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    ")};var iN={kernelName:i.qc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,s=r.alignCorners,c=r.halfPixelCenters,u=r.size,l=Object(o.a)(u,2),d=l[0],f=l[1],p=Object(i.Ud)().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new aN(a.shape,d,f,s,c):new rN(a.shape,d,f,s,c);return n.runWebGLProgram(p,[a],"float32")}},oN=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["dy"],this.outputShape=[],this.outputShape=n;var a=Object(o.a)(n,3),i=a[1],s=a[2],c=Object(o.a)(t,3),u=c[1],l=c[2],d=[r&&u>1?i-1:i,r&&l>1?s-1:s],f=[r&&u>1?u-1:u,r&&l>1?l-1:l],p=d[0]/f[0],h=d[1]/f[1],b=1/p,m=1/h,v=2*Math.ceil(b)+2,g=2*Math.ceil(m)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(".concat(p,");\n        const float widthScale = float(").concat(h,");\n\n        const float invHeightScale = float(").concat(b,");\n        const float invWidthScale = float(").concat(m,");\n\n        const int winHeight = int(").concat(v,");\n        const int winWidth = int(").concat(g,");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= ").concat(u,") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= ").concat(l,") {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), ").concat(i-1,".0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), ").concat(s-1,".0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    ")};var sN={kernelName:i.rc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,i=t.dy,o=r.alignCorners,s=new oN(i.shape,a.shape,o);return n.runWebGLProgram(s,[i],i.dtype)}},cN=function e(t,n,r,a,i){Object(Yr.a)(this,e),this.variableNames=["A"],this.outputShape=[];var s=Object(o.a)(t,4),c=s[0],u=s[1],l=s[2],d=s[3];this.outputShape=[c,n,r,d];var f,p=[a&&n>1?u-1:u,a&&r>1?l-1:l],h=[a&&n>1?n-1:n,a&&r>1?r-1:r],b=a?"0.5":"0.0";f=i?"max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":"vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          ".concat(p[0]/h[0],",\n          ").concat(p[1]/h[1],");\n      const vec2 inputShapeRC = vec2(").concat(u,".0, ").concat(l,".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = ").concat(f,";\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ").concat(b,")));\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    ")},uN=function e(t,n,r,a,i){Object(Yr.a)(this,e),this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var s=Object(o.a)(t,4),c=s[0],u=s[1],l=s[2],d=s[3];this.outputShape=[c,n,r,d];var f,p=[a&&n>1?u-1:u,a&&r>1?l-1:l],h=[a&&n>1?n-1:n,a&&r>1?r-1:r],b=a?"0.5":"0.0";f=i?"max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":"vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode="\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          ".concat(p[0]/h[0],",\n          ").concat(p[1]/h[1],",\n          ").concat(p[1]/h[1],");\n      const vec3 inputShapeRC = vec3(").concat(u,".0, ").concat(l,".0,\n                                     ").concat(l,".0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = ").concat(f,";\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec3 sourceNearestRC = ivec3(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ").concat(b,")));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < ").concat(d-1,";\n        bool hasNextRow = coords.z < ").concat(r-1,";\n\n        vec4 newValue = vec4(\n          getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),\n          hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);\n\n        setOutput(newValue);\n      }\n    ")};var lN={kernelName:i.sc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,s=r.alignCorners,c=r.halfPixelCenters,u=r.size,l=Object(o.a)(u,2),d=l[0],f=l[1],p=Object(i.Ud)().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new uN(a.shape,d,f,s,c):new cN(a.shape,d,f,s,c);return n.runWebGLProgram(p,[a],a.dtype)}},dN=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["dy"],this.outputShape=[],this.outputShape=n;var a=Object(o.a)(n,3),i=a[1],s=a[2],c=Object(o.a)(t,3),u=c[1],l=c[2],d=[r&&u>1?i-1:i,r&&l>1?s-1:s],f=[r&&u>1?u-1:u,r&&l>1?l-1:l],p=d[0]/f[0],h=d[1]/f[1],b=1/p,m=1/h,v=2*Math.ceil(b)+2,g=2*Math.ceil(m)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(".concat(p,");\n        const float widthScale = float(").concat(h,");\n\n        const float invHeightScale = float(").concat(b,");\n        const float invWidthScale = float(").concat(m,");\n\n        const int winHeight = int(").concat(v,");\n        const int winWidth = int(").concat(g,");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= ").concat(u,") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= ").concat(l,") {\n              continue;\n            }\n\n            float sourceFracRow =\n              float(").concat(d[0],") *\n                (float(dyR) / float(").concat(f[0],"));\n\n            float sourceFracCol =\n                float(").concat(d[1],") *\n                  (float(dyC) / float(").concat(f[1],"));\n\n            int sourceNearestRow = int(min(\n                float(int(").concat(i,") - 1),\n                ").concat(r," ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int(").concat(s,") - 1),\n                ").concat(r," ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    ")};var fN={kernelName:i.tc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.images,i=t.dy,o=r.alignCorners,s=new dN(i.shape,a.shape,o);return n.runWebGLProgram(s,[i],i.dtype)}},pN=function e(t,n){Object(Yr.a)(this,e),this.variableNames=["x"];var r=t.length;if(r>4)throw new Error("WebGL backend: Reverse of rank-".concat(r," tensor is not yet supported"));if(this.outputShape=t,1!==r){var a=t.map((function(e,r){return function(e){return-1!==n.indexOf(e)&&1!==t[e]?"".concat(t[e]," - coords[").concat(e,"] - 1"):"coords[".concat(e,"]")}(r)})).join(","),i=Cy(r);this.userCode="\n      void main() {\n        ".concat(i," coords = getOutputCoords();\n        setOutput(getX(").concat(a,"));\n      }\n    ")}else this.userCode="\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX(".concat(t[0]," - coord - 1));\n        }\n      ")},hN=function e(t,n){Object(Yr.a)(this,e),this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;var r=t.length;if(r>4)throw new Error("WebGL backend: Reverse of rank-".concat(r," tensor is not yet supported"));this.outputShape=t;var a=jO("rc",r),i="".concat(a[r-1]," + 1 < ").concat(this.outputShape[r-1]),o="".concat(a[r-2]," + 1 < ").concat(this.outputShape[r-2]),s=Cy(r);function c(e){var r=t.map((function(r,a){return function(e,r){return-1!==n.indexOf(e)&&1!==t[e]?"".concat(t[e]," - ").concat(r[e]," - 1"):"".concat(r[e])}(a,e)})),a=r.join(","),i=r.slice(-2).join(",");return"getChannel(getX(".concat(a,"), vec2(").concat(i,"))")}this.userCode=1===r?"\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX(".concat(t[0]," - rc - 1),\n            ").concat(t[0]," - rc - 1);\n          if(").concat(i,"){\n              result.g = getChannel(getX(").concat(t[0]," - (rc  + 1) - 1),\n                ").concat(t[0]," - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      "):"\n        void main() {\n          ".concat(s," rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = ").concat(function(e){return c(e)}(a.slice()),";\n          if(").concat(i,"){\n            result.g = ").concat(function(e){return e[r-1]="("+e[r-1]+" + 1)",c(e)}(a.slice()),";\n          }\n          if(").concat(o,") {\n            result.b = ").concat(function(e){return e[r-2]="("+e[r-2]+" + 1)",c(e)}(a.slice()),";\n            if(").concat(i,") {\n              result.a = ").concat(function(e){return e[r-1]="("+e[r-1]+" + 1)",e[r-2]="("+e[r-2]+" + 1)",c(e)}(a.slice()),";\n            }\n          }\n          setOutput(result);\n        }\n    ")};var bN={kernelName:i.uc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.dims,s=a.shape.length,c=i.wf.parseAxisParam(o,a.shape);if(0===s)return JO({inputs:{x:a},backend:n});var u=Object(i.Ud)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new hN(a.shape,c):new pN(a.shape,c);return n.runWebGLProgram(u,[a],a.dtype)}},mN=function e(t,n){Object(Yr.a)(this,e),this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];var r=t[1],a=t[2];this.outputShape=t;var i="";i="number"===typeof n?"float outputValue = ".concat(n.toFixed(2),";"):"\n        vec3 fill = vec3(".concat(n.join(","),");\n        float outputValue = fill[coords[3]];"),this.userCode="\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int x = coords[2];\n          int y = coords[1];\n          float coordXFloat = (float(x) - params[0]) * params[3] -\n            (float(y) - params[1]) * params[2];\n          float coordYFloat = (float(x) - params[0]) * params[2] +\n            (float(y) - params[1]) * params[3];\n          int coordX = int(round(coordXFloat + params[0]));\n          int coordY = int(round(coordYFloat + params[1]));\n          ".concat(i,"\n          if(coordX >= 0 && coordX < ").concat(a," && coordY >= 0 && coordY < ").concat(r,") {\n            outputValue = getImage(coords[0], coordY, coordX, coords[3]);\n          }\n          setOutput(outputValue);\n        }\n    ")},vN={kernelName:i.vc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.attrs,r=e.backend,a=t.image,s=n.radians,c=n.fillValue,u=n.center,l=r,d=new mN(a.shape,c),f=i.ud.getImageCenter(u,a.shape[1],a.shape[2]),p=Object(o.a)(f,2),h=[[p[0],p[1],Math.sin(s),Math.cos(s)]];return l.runWebGLProgram(d,[a],a.dtype,h)}},gN=ux({opSnippet:"\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n"}),yN={kernelName:i.wc,backendName:"webgl",kernelFunc:gN},ON=ux({opSnippet:"return inversesqrt(x);",cpuKernelImpl:cO}),xN={kernelName:i.xc,backendName:"webgl",kernelFunc:ON},kN=function e(t,n,r,a,i,o){Object(Yr.a)(this,e),this.variableNames=["updates","indices","defaultValue"],this.outputShape=o;var s=Cy(i.length),c=Cy(o.length),u="";1===r?u="i":2===r&&(u="i, j");var l="getIndices(".concat(u,")"),d="";1===a?d="i":2===a&&(d="i, coords[1]");var f="getUpdates(".concat(d,")"),p=n>1?"strides[j]":"strides";this.userCode="\n        ".concat(s," strides = ").concat(s,"(").concat(i,");\n\n        void main() {\n          ").concat(c," coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < ").concat(t,"; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < ").concat(n,"; j++) {\n              int index = round(").concat(l,");\n              flattenedIndex += index * ").concat(p,";\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += ").concat(f,";\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      ")};var wN={kernelName:i.yc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.indices,o=t.updates,s=r.shape,c=i.ud.calculateShapes(o,a,s),u=c.sliceRank,l=c.numUpdates,d=c.sliceSize,f=c.strides,p=c.outputSize,h=[p/d,d];if(0===p)return n.makeTensorInfo(s,a.dtype);var b=yx({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=yx({inputs:{x:o},backend:n,attrs:{shape:[l,d]}}),v=n.makeTensorInfo([],"float32",new Float32Array([0])),g=new kN(l,u,b.shape.length,m.shape.length,f,h),y=n.runWebGLProgram(g,[m,b,v],m.dtype),O=yx({inputs:{x:y},backend:n,attrs:{shape:s}});return n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(v),O}},jN=function e(t,n,r){var a,i;if(Object(Yr.a)(this,e),this.variableNames=["c","a","b"],this.outputShape=n,r>4)throw Error("Where for rank ".concat(r," is not yet supported"));if(1===r)i="resRC",a="resRC";else{for(var o=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[],c=[],u=0;u<n.length;u++)c.push("".concat(o[u])),u<t&&s.push("".concat(o[u]));a=s.join(),i=c.join()}var l=Cy(r);this.userCode="\n      void main() {\n        ".concat(l," resRC = getOutputCoords();\n        float cVal = getC(").concat(a,");\n        if (cVal >= 1.0) {\n          setOutput(getA(").concat(i,"));\n        } else {\n          setOutput(getB(").concat(i,"));\n        }\n      }\n    ")};var SN={kernelName:i.zc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.condition,a=t.t,o=t.e,s=new jN(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(s,[r,a,o],Object(i.vf)(a.dtype,o.dtype))}},NN=ux({opSnippet:"\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = ".concat(i.ud.SELU_SCALEALPHA,";\n  float scale = ").concat(i.ud.SELU_SCALE,";\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n")}),IN={kernelName:i.Ac,backendName:"webgl",kernelFunc:NN},CN=ux({opSnippet:"return 1.0 / (1.0 + exp(-1.0 * x));"}),TN={kernelName:i.Bc,backendName:"webgl",kernelFunc:CN},EN=ux({opSnippet:"\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n"}),AN={kernelName:i.Cc,backendName:"webgl",kernelFunc:EN},RN=ux({opSnippet:"if (isnan(x)) return x;\n  return sin(x);\n"}),FN={kernelName:i.Dc,backendName:"webgl",kernelFunc:RN},DN=ux({opSnippet:"\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n"}),_N={kernelName:i.Ec,backendName:"webgl",kernelFunc:DN},MN=ux({opSnippet:"\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n"}),zN={kernelName:i.Hc,backendName:"webgl",kernelFunc:MN},LN={kernelName:i.Ic,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.blockShape,s=r.paddings;i.wf.assert(a.shape.length<=4,(function(){return"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet"}));var c=o.reduce((function(e,t){return e*t})),u=[[0,0]];u.push.apply(u,Object(Vn.a)(s));for(var l=1+o.length;l<a.shape.length;++l)u.push([0,0]);var d=[],f=HS({inputs:{x:a},backend:n,attrs:{paddings:u,constantValue:0}}),p=i.ud.getReshaped(f.shape,o,c,!1),h=i.ud.getPermuted(p.length,o.length,!1),b=i.ud.getReshapedPermuted(f.shape,o,c,!1),m=yx({inputs:{x:f},backend:n,attrs:{shape:p}}),v=Tx({inputs:{x:m},backend:n,attrs:{perm:h}}),g=yx({inputs:{x:v},backend:n,attrs:{shape:b}});return d.push(f),d.push(m),d.push(v),d.forEach((function(e){return n.disposeIntermediateTensorInfo(e)})),g}};var PN={kernelName:i.Jc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.indices,a=t.values,i=t.denseShape,s=t.defaultValue;if(1!==i.shape.length)throw new Error("Dense shape must be a vector, saw:\n         ".concat(i.shape));if(2!==r.shape.length)throw new Error("Indices must be a matrix, saw:\n         ".concat(r.shape));if(1!==a.shape.length)throw new Error("Values must be a vector, saw:\n         ".concat(a.shape));if(0!==s.shape.length)throw new Error("Default value must be a scalar, saw:\n        ".concat(s.shape));var c=n.readSync(r.dataId),u=n.readSync(a.dataId),l=n.readSync(i.dataId),d=n.readSync(s.dataId)[0],f=dO(c,r.shape,r.dtype,u,a.dtype,l,d),p=Object(o.a)(f,5),h=p[0],b=p[1],m=p[2],v=p[3],g=p[4];return[n.makeTensorInfo(b,r.dtype,h),n.makeTensorInfo([b[0]],a.dtype,m),n.makeTensorInfo([v.length],"bool",new Uint8Array(v.map((function(e){return Number(e)})))),n.makeTensorInfo([g.length],r.dtype,new Int32Array(g))]}};var BN={kernelName:i.Kc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.inputIndices,a=t.inputShape,i=t.newShape;if(2!==r.shape.length)throw new Error("Input indices should be a matrix but received shape ".concat(r.shape));if(1!==a.shape.length)throw new Error("Input shape should be a vector but received shape ".concat(a.shape));if(1!==i.shape.length)throw new Error("Target shape should be a vector but received shape ".concat(i.shape));var s=Array.from(n.readSync(a.dataId)),c=n.readSync(r.dataId),u=Array.from(n.readSync(i.dataId)),l=fO(c,r.shape,r.dtype,s,u),d=Object(o.a)(l,3),f=d[0],p=d[1],h=d[2];return[n.makeTensorInfo(p,r.dtype,f),n.makeTensorInfo([h.length],i.dtype,new Int32Array(h))]}};var WN={kernelName:i.Lc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.data,a=t.indices,i=t.segmentIds;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.shape.length)throw new Error("Indices should be a vector but received shape\n              ".concat(a.shape));if(1!==i.shape.length)throw new Error("Segment ids should be a vector but received shape\n              ".concat(i.shape));var s=n.readSync(r.dataId),c=n.readSync(a.dataId),u=n.readSync(i.dataId),l=pO(s,r.shape,r.dtype,c,u,!0),d=Object(o.a)(l,2),f=d[0],p=d[1];return n.makeTensorInfo(p,r.dtype,f)}};var UN={kernelName:i.Mc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=t.data,a=t.indices,i=t.segmentIds;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.shape.length)throw new Error("Indices should be a vector but received shape\n             ".concat(a.shape));if(1!==i.shape.length)throw new Error("Segment ids should be a vector but received shape\n             ".concat(i.shape));var s=n.readSync(r.dataId),c=n.readSync(a.dataId),u=n.readSync(i.dataId),l=pO(s,r.shape,r.dtype,c,u),d=Object(o.a)(l,2),f=d[0],p=d[1];return n.makeTensorInfo(p,r.dtype,f)}};var VN={kernelName:i.Nc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.sparseIndices,o=t.sparseValues,s=t.defaultValue,c=r.outputShape,u=i.ud.calculateShapes(o,a,c),l=u.sliceRank,d=u.numUpdates,f=u.strides,p=u.outputSize,h=new kN(d,l,a.shape.length,o.shape.length,f,[p,1],!1),b=n.runWebGLProgram(h,[o,a,s],o.dtype),m=yx({inputs:{x:b},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(b),m}};var HN={kernelName:i.Oc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.numOrSizeSplits,s=r.axis,c=i.wf.parseAxisParam(s,a.shape)[0],u=i.ud.prepareSplitSize(a,o,c),l=a.shape.length,d=new Array(l).fill(0),f=a.shape.slice();return u.map((function(e){var t=Object(Vn.a)(f);t[c]=e;var r=Sk({inputs:{x:a},backend:n,attrs:{begin:d,size:t}});return d[c]+=e,r}))}},GN=ux({opSnippet:"return sqrt(x);"}),qN={kernelName:i.Pc,backendName:"webgl",kernelFunc:GN},KN=ux({opSnippet:"return x * x;"}),XN={kernelName:i.Qc,backendName:"webgl",kernelFunc:KN},YN="return (a - b) * (a - b);",$N=lx({opSnippet:YN,packedOpSnippet:YN}),QN={kernelName:i.Rc,backendName:"webgl",kernelFunc:$N};var ZN={kernelName:i.Sc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.attrs,r=e.backend,a=t.x,i=RO+"\n    return x > 0.0 ? 1.0 : float(".concat(n.alpha,");\n  "),o=new AO(a.shape,i);return r.runWebGLProgram(o,[a],a.dtype)}},JN=function e(t,n,r){Object(Yr.a)(this,e),this.variableNames=["x"],this.outputShape=r;var a=r.length,i=Cy(r.length),o=Cy(r.length),s="";if(1===a)s="coords * strides + begin";else{var c=0;s=r.map((function(e,t){return c++,1===r.length?"coords * strides[".concat(t,"] + begin[").concat(t,"]"):"coords[".concat(c-1,"] * strides[").concat(t,"] + begin[").concat(t,"]")})).join(",")}this.userCode="\n      ".concat(i," begin = ").concat(i,"(").concat(t,");\n      ").concat(i," strides = ").concat(i,"(").concat(n,");\n\n      void main() {\n        ").concat(o," coords = getOutputCoords();\n        setOutput(getX(").concat(s,"));\n      }\n    ")};var eI={kernelName:i.Tc,backendName:"webgl",kernelFunc:function(e){var t,n=e.inputs,r=e.backend,a=e.attrs,o=n.x,s=a.begin,c=a.end,u=a.strides,l=a.beginMask,d=a.endMask,f=a.ellipsisMask,p=a.newAxisMask,h=a.shrinkAxisMask,b=i.af.sliceInfo(o.shape,s,c,u,l,d,f,p,h),m=b.nonStrided,v=b.$begin,g=b.$strides,y=b.size,O=b.newShape,x=b.outShape,k=yx({inputs:{x:o},backend:r,attrs:{shape:O}});if(m){var w=Sk({inputs:{x:k},backend:r,attrs:{begin:v,size:y}});t=yx({inputs:{x:w},backend:r,attrs:{shape:x}}),r.disposeIntermediateTensorInfo(w)}else if(x.some((function(e){return 0===e})))t=r.makeTensorInfo(x,o.dtype,[]);else{if(r.shouldExecuteOnCPU([k])){var j=r.texData.get(k.dataId).values,S=Object(i.zd)(k.shape,k.dtype,j),N=hO(x,S,g,v);t=r.makeTensorInfo(x,k.dtype,N.values)}else{var I=new JN(v,g,x);t=r.runWebGLProgram(I,[k],k.dtype)}}var C=yx({inputs:{x:t},backend:r,attrs:{shape:x}});return r.disposeIntermediateTensorInfo(k),r.disposeIntermediateTensorInfo(t),C}};var tI={kernelName:i.Uc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=r.separator,i=r.nGramWidths,s=r.leftPad,c=r.rightPad,u=r.padWidth,l=r.preserveShortSequences,d=t.data,f=t.dataSplits,p=n.readSync(d.dataId),h=n.readSync(f.dataId),b=bO(p,h,a,i,s,c,u,l),m=Object(o.a)(b,2),v=m[0],g=m[1];return[n.makeTensorInfo([v.length],"string",v),n.makeTensorInfo(f.shape,"int32",g)]}};var nI={kernelName:i.Vc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs.skipEmpty,a=t.input,i=t.delimiter;if("string"!==a.dtype)throw new Error("Input must be of datatype string");if(1!==a.shape.length)throw new Error("Input must be a vector, got shape: ".concat(a.shape));if(0!==i.shape.length)throw new Error("Delimiter must be a scalar, got shape: ".concat(i.shape));var s=n.readSync(a.dataId),c=n.readSync(i.dataId)[0],u=mO(s,c,r),l=Object(o.a)(u,3),d=l[0],f=l[1],p=l[2],h=f.length;return[n.makeTensorInfo([h,2],"int32",d),n.makeTensorInfo([h],"string",f),n.makeTensorInfo([2],"int32",new Int32Array(p))]}};var rI={kernelName:i.Wc,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs.numBuckets,a=t.input;if("string"!==a.dtype)throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");var i=n.readSync(a.dataId),o=vO(i,r);return n.makeTensorInfo(a.shape,"int32",o)}},aI=ux({opSnippet:"return tan(x);"}),iI={kernelName:i.Zc,backendName:"webgl",kernelFunc:aI},oI=ux({opSnippet:"\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n"}),sI={kernelName:i.ad,backendName:"webgl",kernelFunc:oI},cI=function e(t,n){Object(Yr.a)(this,e),this.variableNames=["A"];for(var r=new Array(t.length),a=0;a<r.length;a++)r[a]=t[a]*n[a];this.outputShape=r,this.rank=r.length;var i=Cy(this.rank),o=function(e){var t=e.length;if(t>5)throw Error("Tile for rank ".concat(t," is not yet supported"));if(1===t)return"imod(resRC, ".concat(e[0],")");for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[],a=0;a<e.length;a++)r.push("imod(".concat(n[a],", ").concat(e[a],")"));return r.join()}(t);this.userCode="\n      void main() {\n        ".concat(i," resRC = getOutputCoords();\n        setOutput(getA(").concat(o,"));\n      }\n    ")};function uI(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,o=r.reps;if("string"===a.dtype||a.shape.length>5){var s=n.readSync(a.dataId),c="string"===a.dtype?s.map((function(e){return i.wf.decodeString(e)})):s,u=Object(i.zd)(a.shape,a.dtype,c),l=yO(u,o);return n.makeTensorInfo(l.shape,l.dtype,l.values)}var d=new cI(a.shape,o);return n.runWebGLProgram(d,[a],a.dtype)}var lI={kernelName:i.dd,backendName:"webgl",kernelFunc:uI},dI=function e(t){Object(Yr.a)(this,e),this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=t,this.userCode="\n       void main() {\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int elemIdx = coords[1];\n\n         // We compare elements pair-wise within a group of size 2 * inc.\n         // The comparing rule for each group alternates between ascending\n         // and descending. Within each group, we compare each pair at\n         // positions i and i+inc. To decide whether an element at position i\n         // is x0 or x1, we mod it by 2 * inc, if the result is smaller than\n         // inc, it is in the first half of the group, we denote it as x0,\n         // otherwise we denote it as x1.\n         // For example, as shown in the Bitonic top K paper referenced above,\n         // Figure5(a) shows that element[1] is in the\n         // second half of the group when group size is 2, but it is in the\n         // first half of the group when group size is 4.\n\n         bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;\n         int i = isFirstInPair ? elemIdx : elemIdx - inc;\n\n         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n         int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));\n         float x0 = i0 < n ? getX(batch, i0) : negativeInf;\n         float x1 = i1 < n ? getX(batch, i1) : negativeInf;\n\n         // Denotes which direction indices are in (ascending or descending).\n         bool reverse = imod(elemIdx, 2 * dir) >= dir;\n         bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);\n         if (reverse == isGreater) { // Elements in opposite order of direction\n           int iTemp = i0;\n           i0 = i1;\n           i1 = iTemp;\n         }\n         if (isFirstInPair) {\n            setOutput(float(i0));\n         } else {\n            setOutput(float(i1));\n         }\n       }\n     "},fI=function e(t){Object(Yr.a)(this,e),this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=t,this.userCode="\n    void main() {\n         // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int elemIdx = coords[1];\n\n         // The output size is half of the previous size.\n         // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _ (k=4),\n         // we only need to output the indices at positions |, the indices at\n         // positions _ can be thrown away, see Figure5(b) After Phase 2\n         // (Merge phase) in the Bitonic Top K paper referenced above.\n         // For example, the paper shows we only need to output the orange bars.\n         // The output sequence should look like this | | | | | | | |.\n         // Because the sequence is halved, to map the output index back\n         // to the previous sequence to find the corresponding value,\n         // we need to double the index. When we double the index,\n         // we basically interpolate a position, so 2i looks like\n         // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position\n         // of each 2k positions by - elemIdx % k. E.g. for output at\n         // index 4,5,6,7, we want to get the corresponding element at\n         // original index 8,9,10,11, for output at index 8,9,10,11,\n         // we want to get the corresponding element at original index\n         // 16,17,18,19, so on and so forth.\n\n         int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));\n         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n         int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));\n\n         float x0 = getX(batch, i0);\n         float x1 = i1 < n ? getX(batch, i1) : x0;\n\n         setOutput(x0 >= x1 ? float(i0) : float(i1));\n       }\n     "};function pI(e,t){null!==t&&e.disposeIntermediateTensorInfo(t)}function hI(e){for(var t=1;t<e;)t*=2;return t}var bI={kernelName:i.ed,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.x,s=r.k,c=r.sorted,u=Object(i.Ud)().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=Object(i.Ud)().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),d=a.shape,f=d[d.length-1];if(n.shouldExecuteOnCPU([a])||f<u||s>l){var p=n.readSync(a.dataId),h=OO(p,d,a.dtype,s,c),b=Object(o.a)(h,2),m=b[0],v=b[1];return[n.makeTensorInfo(m.shape,m.dtype,m.values),n.makeTensorInfo(v.shape,v.dtype,v.values)]}if(0===s)return d[d.length-1]=0,[n.makeTensorInfo(d,a.dtype,[]),n.makeTensorInfo(d,"int32",[])];if(1===f)return[a,nj({attrs:{shape:d,dtype:"int32",value:0},backend:n})];var g=n.texData.get(a.dataId),y=null!==g&&g.isPacked,O=y?n.unpackTensor(a):a,x=i.wf.sizeFromShape(d)/f,k=yx({inputs:{x:O},attrs:{shape:[x,f]},backend:n});y&&pI(n,O);for(var w=hI(s),j=hI(f),S=null,N=function(){return null===S?[k,k]:[k,S]},I=function(e,t,r){var a=N(),i=new dI(r),o=[[f],[null===S?1:0],[Number.NEGATIVE_INFINITY],[e],[t]],s=S;S=n.runWebGLProgram(i,a,"int32",o),pI(n,s)},C=1;C<w;C*=2)for(var T=2*C,E=C;E>=1;E/=2)I(T,E,[x,j]);for(var A=j;A>w;A/=2){var R=N(),F=new fI([x,A/2]),D=[[f],[null===S?1:0],[w]],_=S;S=n.runWebGLProgram(F,R,"int32",D),pI(n,_);for(var M=w/2,z=2*M,L=M;L>=1;L/=2)I(z,L,S.shape)}var P=S;S=Sk({inputs:{x:S},backend:n,attrs:{begin:0,size:[x,s]}}),pI(n,P);var B=Oj({inputs:{x:k,indices:S},backend:n,attrs:{axis:1,batchDims:1}});pI(n,k);var W=d.slice(0,-1);W.push(s),P=S,S=yx({inputs:{x:S},attrs:{shape:W},backend:n}),pI(n,P);var U=B;return B=yx({inputs:{x:B},attrs:{shape:W},backend:n}),pI(n,U),[B,S]}},mI=function e(t,n,r,a,i,o){Object(Yr.a)(this,e),this.variableNames=["Image","Transforms"],this.outputShape=o;var s,c="nearest"===r?1:2;switch(a){case"constant":s=1;break;case"reflect":s=2;break;case"wrap":s=3;break;case"nearest":s=4;break;default:s=1}this.userCode="\n            float mapCoord(float outCoord, float len) {\n              float inCoord = outCoord;\n              if(".concat(s," == 2) {\n                if (inCoord < 0.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz2 = 2.0 * len;\n                    if (inCoord < sz2) {\n                      inCoord = sz2 * float(int(float(-inCoord / sz2))) +\n                      inCoord;\n                    }\n                    inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;\n                  }\n                } else if (inCoord > len - 1.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz2 = 2.0 * len;\n                    inCoord -= sz2 * float(int(float(inCoord / sz2)));\n                    if (inCoord >= len) {\n                      inCoord = sz2 - inCoord - 1.0;\n                    }\n                  }\n                }\n                return clamp(inCoord, 0.0, len - 1.0);\n              } else if (").concat(s," == 3) {\n                if (inCoord < 0.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz = len - 1.0;\n                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);\n                  }\n                } else if (inCoord > len - 1.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz = len - 1.0;\n                    inCoord -= len * float(int(float(inCoord / sz)));\n                  }\n                }\n                return clamp(inCoord, 0.0, len - 1.0);\n              } else if (").concat(s," == 4) {\n                return clamp(outCoord, 0.0, len - 1.0);\n              } else {\n                return outCoord;\n              }\n            }\n\n            float readWithFillValue(int batch, int coordY, int coordX,\n              int channel) {\n              float outputValue;\n              if (0 <= coordY && coordY < ").concat(t," && 0 <= coordX && coordX < ").concat(n,") {\n                  outputValue = getImage(batch, coordY, coordX, channel);\n              } else {\n                outputValue = float(").concat(i,");\n              }\n              return outputValue;\n            }\n\n            void main() {\n              ivec4 coords = getOutputCoords();\n              float outputValue;\n              int batch = coords[0];\n              int x = coords[2];\n              int y = coords[1];\n              int channel = coords[3];\n              float xf = float(x);\n              float yf = float(y);\n              float a1 = getTransforms(batch, 0);\n              float a2 = getTransforms(batch, 1);\n              float a3 = getTransforms(batch, 2);\n              float b1 = getTransforms(batch, 3);\n              float b2 = getTransforms(batch, 4);\n              float b3 = getTransforms(batch, 5);\n              float c1 = getTransforms(batch, 6);\n              float c2 = getTransforms(batch, 7);\n              float projection = c1 * xf + c2 * yf + 1.0;\n              if (projection == 0.0) {\n                outputValue = float(").concat(i,");\n              } else {\n                float inX = (a1 * xf + a2 * yf + a3) / projection;\n                float inY = (b1 * xf + b2 * yf + b3) / projection;\n                float mapX = mapCoord(inX, float(").concat(n,"));\n                float mapY = mapCoord(inY, float(").concat(t,"));\n\n                if (").concat(c," == 1) {\n                  int coordY = int(round(mapY));\n                  int coordX = int(round(mapX));\n                  outputValue = readWithFillValue(batch, coordY, coordX,\n                    channel);\n                } else {\n                  float yFloor = floor(mapY);\n                  float xFloor = floor(mapX);\n                  float yCeil = yFloor + 1.0;\n                  float xCeil = xFloor + 1.0;\n                  float valueYFloor = (xCeil - mapX) *\n                  readWithFillValue(batch, int(yFloor), int(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, int(yFloor), int(xCeil), channel);\n                  float valueYCeil = (xCeil - mapX) *\n                  readWithFillValue(batch, int(yCeil), int(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, int(yCeil), int(xCeil), channel);\n                  outputValue = (yCeil - mapY) * valueYFloor +\n                  (mapY - yFloor) * valueYCeil;\n                }\n              }\n              setOutput(outputValue);\n            }\n        ")};var vI={kernelName:i.fd,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.image,i=t.transforms,s=r.interpolation,c=r.fillMode,u=r.fillValue,l=r.outputShape,d=Object(o.a)(a.shape,4),f=d[0],p=d[1],h=d[2],b=d[3],m=null!=l?l:[p,h],v=Object(o.a)(m,2),g=v[0],y=v[1],O=new mI(p,h,s,c,u,[f,g,y,b]);return n.runWebGLProgram(O,[a,i],"float32")}};var gI={kernelName:i.hd,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.attrs,r=e.backend,a=n.axis,i=t.x;Pg(i,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");var o=r.readSync(i.dataId),s=kO(o,a,i.shape,i.dtype),c=s.outputValues,u=s.outputShape,l=s.indices;return[r.makeTensorInfo(u,i.dtype,c),r.makeTensorInfo([l.length],"int32",l)]}};var yI={kernelName:i.id,backendName:"webgl",kernelFunc:function(e){var t=e.inputs,n=e.backend,r=e.attrs,a=t.value,i=r.axis;i<0&&(i+=a.shape.length);for(var o=a,s=o.shape.length,c=a.shape[i],u=new Array(s-1),l=0,d=0;d<s;d++)d!==i&&(u[l++]=o.shape[d]);var f=[],p=new 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