72c304fa7cac16ed19d8bc75a017f17c8073dd2f,parlai/core/torch_generator_agent.py,TorchGeneratorAgent,compute_loss,#TorchGeneratorAgent#Any#Any#,613

Before Change

        // save loss to metrics
        notnull = batch.label_vec.ne(self.NULL_IDX)
        target_tokens = notnull.long().sum().item()
        correct = ((batch.label_vec == preds) * notnull).sum().item()
        self.metrics["correct_tokens"] += correct
        self.metrics["nll_loss"] += loss.item()
        self.metrics["num_tokens"] += target_tokens
        loss /= target_tokens  // average loss per token
        if return_output:
            return (loss, model_output)
        else:

After Change

        scores, preds, *_ = model_output
        score_view = scores.view(-1, scores.size(-1))
        loss = self.criterion(score_view, batch.label_vec.view(-1))
        loss = loss.view(scores.shape[:-1]).sum(dim=1)
        // save loss to metrics
        notnull = batch.label_vec.ne(self.NULL_IDX)
        target_tokens = notnull.long().sum(dim=-1)

Instances