e1861863b2248e4d7d73c12a152e8c035301095d,pytext/torchscript/module.py,ScriptPyTextTwoTowerEmbeddingModule,make_batch,#ScriptPyTextTwoTowerEmbeddingModule#Any#Any#,752

Before Change

        // The next lines performs the following function, which is not supported by TorchScript
        // sorted_mega_batch = sorted(mega_batch,key=lambda element : len(element[argno]))
        mega_batch_class_list = [
            PytextTwoTowerEmbeddingModuleBatchSort(x, argno) for x in mega_batch
        ]
        sorted_mega_batch_class_list = sorted(mega_batch_class_list)
        sorted_mega_batch = [x.be() for x in sorted_mega_batch_class_list]

After Change

        // The next lines sort all cross-request batch elements by the token length of right_.
        // Note that cross-request batch element can in turn be a client batch.
        mega_batch_key_list = [
            (max_tokens(self.right_tensorizer.tokenize(x[0], x[2])), n)
            for (n, x) in enumerate(mega_batch)
        ]
        sorted_mega_batch_key_list = sorted(mega_batch_key_list)
        sorted_mega_batch = [mega_batch[n] for (key, n) in sorted_mega_batch_key_list]

        // TBD: allow model server to specify batch size in goals dictionary
        max_bs: int = 10
        len_mb = len(mega_batch)

Instances