def down_sampling()

in ar-cnn/model.py [0:0]


    def down_sampling(self,
                      layer_input,
                      num_filters,
                      batch_normalization=False,
                      dropout_rate=0):
        '''
        :param: layer_input: Input Layer to the downsampling block
        :param: num_filters: Number of filters
        :param: batch_normalization: Flag to check if batch normalization to be performed
        :param: dropout_rate: To regularize overfitting
        '''
        encoder = layer_input
        for _ in range(self.CONV_PER_LAYER):
            encoder = Conv2D(num_filters, (3, 3),
                             activation='relu',
                             padding='same')(encoder)
            pooling_layer = MaxPooling2D(pool_size=(2, 2))(encoder)
            if dropout_rate:
                pooling_layer = Dropout(dropout_rate)(pooling_layer)
            if batch_normalization:
                pooling_layer = BatchNormalization()(pooling_layer)
        return encoder, pooling_layer