pytext/torchscript/module.py [789:817]:
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        right_dense_feat: List[List[float]],
        left_dense_feat: List[List[float]],
        right_texts: Optional[List[str]] = None,
        left_texts: Optional[List[str]] = None,
        right_tokens: Optional[List[List[str]]] = None,
        left_tokens: Optional[List[List[str]]] = None,
        languages: Optional[List[str]] = None,
    ):
        right_inputs: ScriptBatchInput = ScriptBatchInput(
            texts=resolve_texts(right_texts),
            tokens=squeeze_2d(right_tokens),
            languages=squeeze_1d(languages),
        )
        right_input_tensors = self.right_tensorizer(right_inputs)
        left_inputs: ScriptBatchInput = ScriptBatchInput(
            texts=resolve_texts(left_texts),
            tokens=squeeze_2d(left_tokens),
            languages=squeeze_1d(languages),
        )
        left_input_tensors = self.left_tensorizer(left_inputs)

        right_dense_feat = self.right_normalizer.normalize(right_dense_feat)
        left_dense_feat = self.left_normalizer.normalize(left_dense_feat)
        right_dense_tensor = torch.tensor(right_dense_feat, dtype=torch.float)
        left_dense_tensor = torch.tensor(left_dense_feat, dtype=torch.float)
        if self.right_tensorizer.device != "":
            right_dense_tensor = right_dense_tensor.to(self.right_tensorizer.device)
        if self.left_tensorizer.device != "":
            left_dense_tensor = left_dense_tensor.to(self.left_tensorizer.device)
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pytext/torchscript/module.py [847:875]:
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        right_dense_feat: List[List[float]],
        left_dense_feat: List[List[float]],
        right_texts: Optional[List[str]] = None,
        left_texts: Optional[List[str]] = None,
        right_tokens: Optional[List[List[str]]] = None,
        left_tokens: Optional[List[List[str]]] = None,
        languages: Optional[List[str]] = None,
    ):
        right_inputs: ScriptBatchInput = ScriptBatchInput(
            texts=resolve_texts(right_texts),
            tokens=squeeze_2d(right_tokens),
            languages=squeeze_1d(languages),
        )
        right_input_tensors = self.right_tensorizer(right_inputs)
        left_inputs: ScriptBatchInput = ScriptBatchInput(
            texts=resolve_texts(left_texts),
            tokens=squeeze_2d(left_tokens),
            languages=squeeze_1d(languages),
        )
        left_input_tensors = self.left_tensorizer(left_inputs)

        right_dense_feat = self.right_normalizer.normalize(right_dense_feat)
        left_dense_feat = self.left_normalizer.normalize(left_dense_feat)
        right_dense_tensor = torch.tensor(right_dense_feat, dtype=torch.float)
        left_dense_tensor = torch.tensor(left_dense_feat, dtype=torch.float)
        if self.right_tensorizer.device != "":
            right_dense_tensor = right_dense_tensor.to(self.right_tensorizer.device)
        if self.left_tensorizer.device != "":
            left_dense_tensor = left_dense_tensor.to(self.left_tensorizer.device)
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