TheNeuralBit commented on code in PR #17470:
URL: https://github.com/apache/beam/pull/17470#discussion_r870606313
##########
sdks/python/apache_beam/ml/inference/pytorch.py:
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@@ -45,11 +46,22 @@ def run_inference(self, batch: List[torch.Tensor],
This method stacks the list of Tensors in a vectorized format to optimize
the inference call.
"""
-
- batch = torch.stack(batch)
- if batch.device != self._device:
- batch = batch.to(self._device)
- predictions = model(batch)
+ if isinstance(batch[0], dict):
Review Comment:
Fair point - another option that @robertwb brought up offline would be to
have multiple implementations, e.g. one for the single-argument special-case,
and another for the **kwargs case (I'm not asking you to do this now, it's just
something to think about)
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