收敛最快的魔改ESPCN, DepthwiseConv2D

原创
2023/02/25 17:58
阅读数 90
    input_image = Input(shape=(None, None, self.channels), name='x')
    x = DepthwiseConv2D( 3, depth_multiplier= int(64 / self.channels), kernel_initializer="he_normal",
               padding='same', activation="tanh", name="conv1")(input_image)
    x = DepthwiseConv2D(5, kernel_initializer="he_normal",
               padding='same', activation="relu", name="conv2")(x)
    x = Conv2D(self.scale_factor**2*self.channels, 3, kernel_initializer="he_normal",
               padding='same', activation="relu", name="conv3")(x)
    y = tf.nn.depth_to_space(x, self.scale_factor, name="shuffle")
    model = Model(inputs=input_image, outputs=y)
    model.summary()
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