aws / deep-learning-containers

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/deep-learning-containers-images.html
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HuggingFace Pytorch Inference 2.1.0 [Patch] #4102

Closed ErnevSharma closed 4 weeks ago

ErnevSharma commented 2 months ago

dlc_developer_config.toml { 'build': { 'build_frameworks': [ '_home_shaernev_workspace_deep-learning-containers_huggingface_pytorch'], 'build_inference': True, 'build_training': False}, 'buildspec_override': { 'dlc-pr--home-shaernev-workspace-deep-learning-containers-huggingface-pytorch-inference': '/home/shaernev/workspace/deep-learning-containers/huggingface/pytorch/inference/buildspec.yml'}, 'dev': { 'deep_canary_mode': False, 'graviton_mode': False, 'neuronx_mode': False}, 'test': { 'ec2_tests': True, 'ecs_tests': True, 'eks_tests': True, 'sagemaker_local_tests': True, 'sagemaker_remote_tests': True, 'sanity_tests': True}}

GitHub Issue #, if available:

Note:

Description

Tests run

NOTE: By default, docker builds are disabled. In order to build your container, please update dlc_developer_config.toml and specify the framework to build in "build_frameworks"

Confused on how to run tests? Try using the helper utility... Assuming your remote is called `origin` (you can find out more with `git remote -v`)... - Run default builds and tests for a particular buildspec - also commits and pushes changes to remote; Example: `python src/prepare_dlc_dev_environment.py -b -cp origin` - Enable specific tests for a buildspec or set of buildspecs - also commits and pushes changes to remote; Example: `python src/prepare_dlc_dev_environment.py -b -t sanity_tests -cp origin` - Restore TOML file when ready to merge `python src/prepare_dlc_dev_environment.py -rcp origin`

NOTE: If you are creating a PR for a new framework version, please ensure success of the standard, rc, and efa sagemaker remote tests by updating the dlc_developer_config.toml file:

Expand - [ ] `sagemaker_remote_tests = true` - [ ] `sagemaker_efa_tests = true` - [ ] `sagemaker_rc_tests = true` **Additionally, please run the sagemaker local tests in at least one revision:** - [ ] `sagemaker_local_tests = true`

Formatting

DLC image/dockerfile

Builds to Execute

Expand Fill out the template and click the checkbox of the builds you'd like to execute *Note: Replace with with the major.minor framework version (i.e. 2.2) you would like to start.* - [ ] build_pytorch_training__sm - [ ] build_pytorch_training__ec2 - [ ] build_pytorch_inference__sm - [ ] build_pytorch_inference__ec2 - [ ] build_pytorch_inference__graviton - [ ] build_tensorflow_training__sm - [ ] build_tensorflow_training__ec2 - [ ] build_tensorflow_inference__sm - [ ] build_tensorflow_inference__ec2 - [ ] build_tensorflow_inference__graviton

Additional context

PR Checklist

Expand - [ ] I've prepended PR tag with frameworks/job this applies to : [mxnet, tensorflow, pytorch] | [ei/neuron/graviton] | [build] | [test] | [benchmark] | [ec2, ecs, eks, sagemaker] - [ ] If the PR changes affects SM test, I've modified dlc_developer_config.toml in my PR branch by setting sagemaker_tests = true and efa_tests = true - [ ] If this PR changes existing code, the change fully backward compatible with pre-existing code. (Non backward-compatible changes need special approval.) - [ ] (If applicable) I've documented below the DLC image/dockerfile this relates to - [ ] (If applicable) I've documented below the tests I've run on the DLC image - [ ] (If applicable) I've reviewed the licenses of updated and new binaries and their dependencies to make sure all licenses are on the Apache Software Foundation Third Party License Policy Category A or Category B license list. See [https://www.apache.org/legal/resolved.html](https://www.apache.org/legal/resolved.html). - [ ] (If applicable) I've scanned the updated and new binaries to make sure they do not have vulnerabilities associated with them. #### NEURON/GRAVITON Testing Checklist * When creating a PR: - [ ] I've modified `dlc_developer_config.toml` in my PR branch by setting `neuron_mode = true` or `graviton_mode = true` #### Benchmark Testing Checklist * When creating a PR: - [ ] I've modified `dlc_developer_config.toml` in my PR branch by setting `ec2_benchmark_tests = true` or `sagemaker_benchmark_tests = true`

Pytest Marker Checklist

Expand - [ ] (If applicable) I have added the marker `@pytest.mark.model("")` to the new tests which I have added, to specify the Deep Learning model that is used in the test (use `"N/A"` if the test doesn't use a model) - [ ] (If applicable) I have added the marker `@pytest.mark.integration("")` to the new tests which I have added, to specify the feature that will be tested - [ ] (If applicable) I have added the marker `@pytest.mark.multinode()` to the new tests which I have added, to specify the number of nodes used on a multi-node test - [ ] (If applicable) I have added the marker `@pytest.mark.processor(<"cpu"/"gpu"/"eia"/"neuron">)` to the new tests which I have added, if a test is specifically applicable to only one processor type

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license. I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

github-actions[bot] commented 1 month ago

This PR has been marked stale as a result of being open for 30 days without activity or updates. Please remove the stale label or comment in order to keep this open, otherwise the PR will be closed in 5 days.

github-actions[bot] commented 4 weeks ago

This PR has had no activity or updates in the last 5 days since being marked stale. Closing this PR as a result.