torchbiggraph/losses.py [92:103]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    def forward(
        self,
        pos_scores: FloatTensorType,
        neg_scores: FloatTensorType,
        weight: Optional[FloatTensorType],
    ) -> FloatTensorType:
        num_pos = match_shape(pos_scores, -1)
        num_neg = match_shape(neg_scores, num_pos, -1)

        # FIXME Workaround for https://github.com/pytorch/pytorch/issues/15223.
        if num_pos == 0 or num_neg == 0:
            return torch.zeros((), device=pos_scores.device, requires_grad=True)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



torchbiggraph/losses.py [130:142]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    def forward(
        self,
        pos_scores: FloatTensorType,
        neg_scores: FloatTensorType,
        weight: Optional[FloatTensorType],
    ) -> FloatTensorType:
        num_pos = match_shape(pos_scores, -1)
        num_neg = match_shape(neg_scores, num_pos, -1)

        # FIXME Workaround for https://github.com/pytorch/pytorch/issues/15870
        # and https://github.com/pytorch/pytorch/issues/15223.
        if num_pos == 0 or num_neg == 0:
            return torch.zeros((), device=pos_scores.device, requires_grad=True)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -