networks.py 文件源码

def _conv_block(layer, num_conv_layers, num_filters):
        """Build a conv block on top of inputs

        :param inputs: Keras Layer object representing the VGG net up to this
         point
        :param num_conv_layers: int for the number of convolutional layers to
         include in this block
        :param num_filters: int for the number of filters per convolutional
         layer
        """

        for _ in  range(num_conv_layers - 1):
            layer = Conv2D(
                filters=num_filters, kernel_size=(3, 3), padding='same',
                activation='relu'
            )(layer)
        layer = MaxPooling2D(pool_size=(2, 2), strides=(2, 2))(layer)

        return layer