[
https://issues.apache.org/jira/browse/BEAM-14337?focusedWorklogId=777807&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-777807
]
ASF GitHub Bot logged work on BEAM-14337:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 02/Jun/22 19:42
Start Date: 02/Jun/22 19:42
Worklog Time Spent: 10m
Work Description: yeandy commented on code in PR #17470:
URL: https://github.com/apache/beam/pull/17470#discussion_r888353350
##########
sdks/python/apache_beam/ml/inference/sklearn_inference.py:
##########
@@ -42,8 +42,8 @@ class ModelFileType(enum.Enum):
class SklearnInferenceRunner(InferenceRunner):
- def run_inference(self, batch: List[numpy.ndarray],
- model: Any) -> Iterable[PredictionResult]:
+ def run_inference(self, batch: List[numpy.ndarray], model: Any,
+ **kwargs) -> Iterable[PredictionResult]:
Review Comment:
Actually, I get this error
```
error: Signature of "run_inference" incompatible with supertype
"InferenceRunner"
```
I think that happens when I take out `**kwargs`. Let me add it back and see
if the error persists.
Issue Time Tracking
-------------------
Worklog Id: (was: 777807)
Time Spent: 7h 50m (was: 7h 40m)
> Support **kwargs for PyTorch models.
> ------------------------------------
>
> Key: BEAM-14337
> URL: https://issues.apache.org/jira/browse/BEAM-14337
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-py-core
> Reporter: Anand Inguva
> Assignee: Andy Ye
> Priority: P2
> Time Spent: 7h 50m
> Remaining Estimate: 0h
>
> Some models in Pytorch instantiating from torch.nn.Module, has extra
> parameters in the forward function call. These extra parameters can be passed
> as Dict or as positional arguments.
> Example of PyTorch models supported by Hugging Face ->
> [https://huggingface.co/bert-base-uncased]
> [Some torch models on Hugging
> face|https://github.com/huggingface/transformers/blob/main/src/transformers/models/bert/modeling_bert.py]
> Eg:
> [https://huggingface.co/docs/transformers/model_doc/bert#transformers.BertModel]
> {code:java}
> inputs = {
> input_ids: Tensor1,
> attention_mask: Tensor2,
> token_type_ids: Tensor3,
> }
> model = BertModel.from_pretrained("bert-base-uncased") # which is a
> # subclass of torch.nn.Module
> outputs = model(**inputs) # model forward method should be expecting the keys
> in the inputs as the positional arguments.{code}
>
> [Transformers|https://pytorch.org/hub/huggingface_pytorch-transformers/]
> integrated in Pytorch is supported by Hugging Face as well.
>
--
This message was sent by Atlassian Jira
(v8.20.7#820007)
