def forward()

in neural/model.py [0:0]

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

    def forward(self, meg, forcings, subject_id):
        forcings = dict(forcings)
        batch, _, length = meg.size()
        inputs = []

        mask = self.get_meg_mask(meg, forcings)
        meg = meg * mask
        inputs += [meg, mask]

        if self.subject_embedding is not None:
            subject = self.subject_embedding(subject_id)
            inputs.append(subject.view(batch, -1, 1).expand(-1, -1, length))

        if self.forcing_dims:
            _, forcings = zip(*sorted([(k, v)
                                       for k, v in forcings.items() if k in self.forcing_dims]))
        else:
            forcings = {}

        inputs.extend(forcings)

        x = th.cat(inputs, dim=1)
        x = self.pad(x)
        x = self.encoder(x)
        if self.lstm is not None:
            x = x.permute(2, 0, 1)
            x, _ = self.lstm(x)
            x = x.permute(1, 2, 0)
        out = self.decoder(x)
        return center_trim(out, length)