22cb76a3479ceba89addb1f467c2dd573cb29026,pytext/torchscript/module.py,ScriptPyTextEmbeddingModule,make_prediction,#ScriptPyTextEmbeddingModule#,283

Before Change

        //   cross-request batches and client side
        //   batches into a cross-request list of
        //   client-side batch tensors
        start = 0
        for elems in client_batch:
            end = start + elems
            res_list.append(flat_result.narrow(0, start, elems))
            start = end

        return res_list

After Change

            raise RuntimeError("Parameter type unsupported")

        // if torch.jit.isinstance(flat_result, torch.Tensor):
        if isinstance(flat_result, torch.Tensor):
            // destructure flat result tensor combining
            //   cross-request batches and client side
            //   batches into a cross-request list of
            //   client-side batch tensors
            return destructure_tensor(client_batch, flat_result)
        else:
            // destructure result list of any result type combining
            //   cross-request batches and client side
            //   batches into a cross-request list of
            //   client-side result lists
            result_texts_any_list: List[Any] = torch.jit.annotate(List[Any], [])
            for v in flat_result:
                result_texts_any_list.append(v)

            return destructure_any_list(client_batch, result_texts_any_list)

    @torch.jit.script_method
    def make_batch(
        self,
        mega_batch: List[

Instances