def forward()

in inception.py [0:0]

• 12 lines of code
• 6 McCabe index (conditional complexity)

    def forward(self, inp):
        """Get Inception feature maps

        Parameters
        ----------
        inp : torch.autograd.Variable
            Input tensor of shape Bx3xHxW. Values are expected to be in
            range (0, 1)

        Returns
        -------
        List of torch.autograd.Variable, corresponding to the selected output
        block, sorted ascending by index
        """
        outp = []
        x = inp

        # if self.resize_input:
        #     x = F.interpolate(x,
        #                       size=(299, 299),
        #                       mode='bilinear',
        #                       align_corners=False)

        if self.normalize_input:
            x = 2 * x - 1  # Scale from range (0, 1) to range (-1, 1)

        for idx, block in enumerate(self.blocks):
            x = block(x)
            if idx in self.output_blocks:
                outp.append(x)

            if idx == self.last_needed_block:
                break

        return outp