Comments (2)
SamShowalter
commented on July 17, 2024
Any update on this? I am also having these issues with both torch versions 1.9 and 1.10 and my code is not compatible with the older images.
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setu4993
commented on July 17, 2024
@SamShowalter : I didn't get any traction here, but after raising it AWS Support, they did tell me a couple weeks ago (and I have since verified) that logs work fine for PyTorch 1.10.2 and PyTorch 1.11 images. They were released / updated in the last couple months according to this doc.
We also saw the same issue of missing logs on 1.9 images, but have transitioned to 1.10 / 1.11, so haven't followed up.
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Related Issues (20)
- MultiDataModel fails at installing requirements.txt
- How do I access Custom Attributes from the model during inference? HOT 1
- Serving a model using custom container, instance run of disk HOT 4
- Need for a minimum reproducible example in readme.md
- Launch TorchServe without repackaging model contents HOT 5
- Batch Inference does not work when using the default handler
- add environment variable "OMP_NUM_THREADS"
- Document how to locally run the container HOT 2
- using cuda enabled pytorch image
- how to use gpu in sagemaker instance HOT 1
- Is this Dockerfile compatible with sagemaker elastic inference
- MMS mode in inference does not support in GPU instance
- [Question] Using model.mar with built-in handler script
- Specify batch size for MME
- Prepend `code_dir` to `sys.path` rather than `append`
- Incorrect reporting of memory utilisation
- Documentation for inference.py `transform_fn`
- Reuse the requirements.txt installation logic from sagemaker-inference-toolkit
- ModuleNotFoundError: Sagemaker only copies entry_point file to /opt/ml/code/ instead of the holy-cloned source code
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