aws / aws/sagemaker-tensorflow-extensions
s3PipeDataset example
- Dominant language
- C++
- Stars
- 54
- Forks
- 39
- PR merge metrics
- No merged PRs in 30d
Description
**What did you find confusing? Please describe.**
I have been trying to start a Sagemaker job with s3pipedataset using TensorFlow or PyTorch but so far I have not been successful. Also, I think pipe mode doesn't work locally.
Is there some documentation or a notebook for end-to-end training using s3pipedataset?
Or at least provide some datasets already stored in PipeDatasetFormat that can be directly loaded into a TensorFlow or PyTorch model.
If possible can you guys also share some Image Dataset for the Computer Vision example?
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**Describe how documentation can be improved**
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**Additional context**
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Contributor guide
Research direction
No files, tests, or entry points are named. Review the existing SageMaker TensorFlow extensions documentation and examples first, then narrow the request to one end-to-end s3pipedataset workflow; completion would require a documented, reproducible TensorFlow or PyTorch example with a stated dataset and expected training result.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pytorch, tensorflow
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100