fdfdbec9e2f2eccfbdd331ae8d165d3ce05bcb73,fairseq/models/fairseq_model.py,BaseFairseqModel,get_normalized_probs,#BaseFairseqModel#Any#Any#Any#,46

Before Change

        if hasattr(self, "decoder"):
            return self.decoder.get_normalized_probs(net_output, log_probs, sample)
        elif torch.is_tensor(net_output):
            logits = net_output.float()
            if log_probs:
                return F.log_softmax(logits, dim=-1)
            else:
                return F.softmax(logits, dim=-1)
        raise NotImplementedError

After Change

        sample: Optional[Dict[str, Tensor]] = None,
    ):
        Get normalized probabilities (or log probs) from a net"s output.
        return self.get_normalized_probs_scriptable(net_output, log_probs, sample)

    // TorchScript doesn"t support super() method so that the scriptable Subclass
    // can"t access the base class model in Torchscript.
    // Current workaround is to add a helper function with different name and

Instances