aws / aws/sagemaker-huggingface-inference-toolkit
Adjust request body data structure for numpy.ndarray for pipeline.
- Dominant language
- Python
- Stars
- 270
- Forks
- 60
- PR merge metrics
- No merged PRs in 30d
Description
It's related to https://github.com/huggingface/transformers/issues/19743.
I think converting logic should be implemented.
In this toolkit's implementation, request body type should be json dict, but many pipelines does not accept list but np.ndarray. With SageMaker's serializer we cannot realize that.
Contributor guide
Research direction
Start by tracing the request-body handling and SageMaker serializer behavior described in the issue, then read the linked Transformers issue for the related pipeline expectations. Done means the toolkit can convert request data into the structure required by pipelines that accept numpy.ndarray rather than lists.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, numpy, python
- Domain
- api, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100