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- import tensorflow as tf
- from tensorflow.keras.models import Sequential
- from tensorflow.keras.layers import Layer, Conv2D, BatchNormalization, ReLU, Activation
- class LRASPP(Layer):
- def __init__(self, out_channels: int):
- super().__init__()
- self.aspp1 = Sequential([
- Conv2D(out_channels, 1, use_bias=False),
- BatchNormalization(momentum=0.1, epsilon=1e-5),
- ReLU()
- ])
- self.aspp2 = Conv2D(out_channels, 1, use_bias=False, activation='sigmoid')
-
- def call(self, x):
- x1 = self.aspp1(x)
- x2 = self.aspp2(tf.reduce_mean(x, axis=[1, 2], keepdims=True))
- return x1 * x2
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