def get_down_sampler()

in sagemaker/src/handwriting_line_recognition.py [0:0]

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

    def get_down_sampler(self, num_filters):
        '''
        Creates a two-stacked Conv-BatchNorm-Relu and then a pooling layer to
        downsample the image features by half.
        
        Parameters
        ----------
        num_filters: int
            To select the number of filters in used the downsampling convolutional layer.
        Returns
        -------
        network: gluon.nn.HybridSequential
            The downsampler network that decreases the width and height of the image features by half.
        
        '''
        out = gluon.nn.HybridSequential()
        with out.name_scope():
            for _ in range(self.num_downsamples):
                out.add(gluon.nn.Conv2D(num_filters, 3, strides=1, padding=1))
                out.add(gluon.nn.BatchNorm(in_channels=num_filters))
                out.add(gluon.nn.Activation('relu'))
            out.add(gluon.nn.MaxPool2D(2))
            out.collect_params().initialize(mx.init.Normal(), ctx=self.ctx)
        out.hybridize()
        return out