def forward()

in pytorchvideo/models/resnet.py [0:0]

• 15 lines of code
• 9 McCabe index (conditional complexity)

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        # Explicitly forward every layer.
        # Branch2a, for example Tx1x1, BN, ReLU.
        x = self.conv_a(x)
        if self.norm_a is not None:
            x = self.norm_a(x)
        if self.act_a is not None:
            x = self.act_a(x)

        # Branch2b, for example 1xHxW, BN, ReLU.
        x = self.conv_b(x)
        if self.norm_b is not None:
            x = self.norm_b(x)
        if self.act_b is not None:
            x = self.act_b(x)

        # Branch2c, for example 1x1x1, BN.
        x = self.conv_c(x)
        if self.norm_c is not None:
            x = self.norm_c(x)
        return x