def forward()

in src/model.py [0:0]

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

    def forward(self, hidden_states, attention_mask, position_bias, **kwargs):
        if self.use_checkpoint and self.training:
            kwargs = {k: v for k, v in kwargs.items() if v is not None}
            def custom_forward(*inputs):
                output = self.module(*inputs, **kwargs)
                empty = torch.tensor(
                    [],
                    dtype=torch.float,
                    device=output[0].device,
                    requires_grad=True)
                output = tuple(x if x is not None else empty for x in output)
                return output

            output = torch.utils.checkpoint.checkpoint(
                custom_forward,
                hidden_states,
                attention_mask,
                position_bias
            )
            output = tuple(x if x.size() != 0 else None for x in output)
        else:
            output = self.module(hidden_states, attention_mask, position_bias, **kwargs)
        return output