def forward()

in fast_grad_conv.py [0:0]

• 18 lines of code
• 3 McCabe index (conditional complexity)

    def forward(self, x):
        if self.train:
            del self.expanded_weight
            del self.expanded_bias
            batch_size = x.size(0)
            self.expanded_weight, self.expanded_bias = FastGradConv2dFunction.apply(self.weight, self.bias, batch_size)
            self.expanded_weight.requires_grad_(True)
            self.expanded_weight.retain_grad()
            if self.expanded_bias is not None:
                self.expanded_bias.requires_grad_(True)
                self.expanded_bias.retain_grad()
            output = F.conv2d(x.view(1, -1, x.size(2), x.size(3)), self.expanded_weight, bias=self.expanded_bias,
                    stride=self.stride, padding=self.padding, dilation=self.dilation,
                    groups=batch_size)
            return output.view(x.size(0), -1, output.size(2), output.size(3))
        else:
            return F.conv2d(x, self.weight, self.bias, stride=self.stride,
                    padding=self.padding, dilation=self.dilation)