def up_sampling()

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

• 23 lines of code
• 4 McCabe index (conditional complexity)

    def up_sampling(self,
                    layer_input,
                    skip_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
        '''
        decoder = concatenate(
            [UpSampling2D(size=(2, 2))(layer_input), skip_input])
        if batch_normalization:
            decoder = BatchNormalization()(decoder)
        for _ in range(self.CONV_PER_LAYER):
            decoder = Conv2D(num_filters, (3, 3),
                             activation='relu',
                             padding='same')(decoder)

        if dropout_rate:
            decoder = Dropout(dropout_rate)(decoder)
        return decoder