src/transformers/pipelines/base.py/Pipeline/_ensure_tensor_on_device
class Pipeline:    def _ensure_tensor_on_device(self, inputs, device):
        if isinstance(inputs, ModelOutput):
            return ModelOutput(
                {name: self._ensure_tensor_on_device(tensor, device) for name, tensor in inputs.items()}
            )
        elif isinstance(inputs, dict):
            return {name: self._ensure_tensor_on_device(tensor, device) for name, tensor in inputs.items()}
        elif isinstance(inputs, UserDict):
            return UserDict({name: self._ensure_tensor_on_device(tensor, device) for name, tensor in inputs.items()})
        elif isinstance(inputs, list):
            return [self._ensure_tensor_on_device(item, device) for item in inputs]
        elif isinstance(inputs, tuple):
            return tuple([self._ensure_tensor_on_device(item, device) for item in inputs])
        elif isinstance(inputs, torch.Tensor):
            if device == torch.device("cpu") and inputs.dtype in {torch.float16, torch.bfloat16}:
                inputs = inputs.float()
            return inputs.to(device)
        else:
            return inputs