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update documentation for recent releases #3932
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@@ -254,12 +254,14 @@ HuggingFace Neuron Inference Containers | |||
|------------------------------------------------------------------|-------------------|-----------|----------------------------|-----------------------|----------------------------------------------------------------------------------------------------------------------------------------------| | |||
|PyTorch 1.10.2 with Neuron Inference and HuggingFace transformers |Neuron 1.19.1 |inference |inf1 |3.7 (py37) |763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference-neuron:1.10.2-transformers4.20.1-neuron-py37-sdk1.19.1-ubuntu18.04 | | |||
|PyTorch 1.13.1 with NeuronX Inference and HuggingFace transformers |Neuron 2.15.0 |inference |inf2/trn1 |3.10 (py310) |763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference-neuronx:1.13.1-transformers4.34.1-neuronx-py310-sdk2.15.0-ubuntu20.04 | | |||
|PyTorch 2.1.2 with NeuronX Inference and HuggingFace transformers |Neuron 2.18.0 |inference |inf2/trn1 |3.10 (py310) |763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference-neuronx:2.1.2-transformers4.36.2-neuronx-py310-sdk2.18.0-ubuntu20.04 | | |||
|
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HuggingFace Neuron Training Containers | |||
=============================== | |||
|Framework |Neuron SDK Version |Job Type |Supported EC2 Instance Type |Python Version Options |Example URL | | |||
|------------------------------------------------------------------|-------------------|-----------|----------------------------|-----------------------|----------------------------------------------------------------------------------------------------------------------------------------------| | |||
|PyTorch 1.13.1 with NeuronX Training and HuggingFace transformers |Neuron 2.15.0 |training |trn1 |3.10 (py310) |763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training-neuronx:1.13.1-transformers4.34.1-neuronx-py310-sdk2.15.0-ubuntu20.04 | |
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Do we still need to keep the old ones?
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No, removed, thanks
ningziwen
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haixiw
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May 22, 2024
commit 0fc43df Author: Shantanu Tripathi <shantanutripathi237@gmail.com> Date: Wed May 22 14:22:16 2024 -0700 [Build][Test] Re-enable AutoPatching for PT1.13 images (aws#3938) * Re-enable AutoPatching for PT1.13 images * Change to 1.13 * Revert temp changes commit 20fc557 Author: Adam Kozdrowicz <akozdrowicz@gmail.com> Date: Wed May 22 16:47:06 2024 -0400 resolve triton import error (aws#3939) Resolve triton import error commit e12ddd2 Author: Junpu Fan <junpu@amazon.com> Date: Wed May 22 13:23:03 2024 -0700 fix triton version in pt2.2 inference gpu images (aws#3954) * fix triton version commit 819ee20 Author: Junpu Fan <junpu@amazon.com> Date: Wed May 22 10:05:56 2024 -0700 Fix triton version pt 21 inf (aws#3952) * Fix triton version * dev config * fix arg * Revert "dev config" This reverts commit aa4ba23. commit 4271d84 Author: Sirut Buasai <73297481+sirutBuasai@users.noreply.github.com> Date: Tue May 21 16:08:48 2024 -0700 Fix PT 2.1 TE Test (aws#3947) * Fix PT 2.1 TE Test * test te on p5 * skip efa * revert onnxruntime version * update onnxruntime to 1.18 * revert onnxruntim version to be p5 compatible * disable onnx test * test te on p4 * revert skip commit 42ece6a Author: Junpu Fan <junpu@amazon.com> Date: Tue May 21 15:03:13 2024 -0700 Allowlist requests 2.31.0 safety finding (aws#3949) * allowlisting requests safety id 71064 commit 68f27de Author: Sally Seok <49303563+sallyseok@users.noreply.github.com> Date: Tue May 21 11:53:34 2024 -0700 Upgrade torchserve to 0.11.0 in PT 2.1 and 2.2 graviton (aws#3926) * Upgrade torchserve to 0.11.0 in PT 2.1 and 2.2 graviton * address CVEs * fix typo * only run 2.1 autopatch regression test * upgrade pyopenssl and rerun tests * run tests for pt2.2 * execute SM local mode tests with updated test requirements * run pt2.1 sm local test; don't run package regression tests * revert toml --------- Co-authored-by: arjkesh <33526713+arjkesh@users.noreply.github.com> commit 9bd5123 Author: Junpu Fan <junpu@amazon.com> Date: Tue May 21 10:16:07 2024 -0700 [PT2.1][SageMaker][X86] torchserve 0.11.0 update (aws#3930) * torchserve 0.11.0 update * upgrade infernece toolkit to 2.0.23 --------- Co-authored-by: arjkesh <33526713+arjkesh@users.noreply.github.com> commit 62c6175 Author: Haotian An <33510317+Captainia@users.noreply.github.com> Date: Tue May 21 11:56:31 2024 -0400 update documentation for recent releases (aws#3932) * update documentation for recent releases * remove old imgs
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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"
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:
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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
black -l 100
on my code (formatting tool: https://black.readthedocs.io/en/stable/getting_started.html)DLC image/dockerfile
Builds to Execute
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Click the checkbox to enable a build to execute upon merge.
Note: By default, pipelines are set to "latest". Replace with major.minor framework version if you do not want "latest".
Additional context
PR Checklist
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NEURON/GRAVITON Testing Checklist
dlc_developer_config.toml
in my PR branch by settingneuron_mode = true
orgraviton_mode = true
Benchmark Testing Checklist
dlc_developer_config.toml
in my PR branch by settingec2_benchmark_tests = true
orsagemaker_benchmark_tests = true
Pytest Marker Checklist
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@pytest.mark.model("<model-type>")
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)@pytest.mark.integration("<feature-being-tested>")
to the new tests which I have added, to specify the feature that will be tested@pytest.mark.multinode(<integer-num-nodes>)
to the new tests which I have added, to specify the number of nodes used on a multi-node test@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 typeBy 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.