yeandy commented on code in PR #21868:
URL: https://github.com/apache/beam/pull/21868#discussion_r898253546
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sdks/python/apache_beam/ml/inference/pytorch_inference.py:
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@@ -190,6 +194,10 @@ def run_inference(
For the same key across all examples, this will stack all Tensors values
in a vectorized format to optimize the inference call.
+ Args:
+ batch: A sequence of Tensors.
+ model: A pytorch model.
Review Comment:
```suggestion
batch: A sequence of keyed Tensors. These Tensors should be batchable,
as this method will call `torch.stack()` and pass in batched Tensors with
dimensions (batch_size, n_features, etc.) into the model's forward() function.
model: A PyTorch model.
inference_args: Non-batchable arguments required as inputs to the
model's forward() function. Unlike Tensors in `batch`, these parameters will
not be dynamically batched
```
@AnandInguva Can you review my wording here?
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