Consolidate smdistributed and pytorchddp launcher

[sirutBuasai]

GitHub Issue #, if available:

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Description

Given SageMaker PythonSDK launcher consolidation in aws/sagemaker-python-sdk#4698, pytorchddp and smdistributed launcher are now behaviorally the same. Moving forward, DLC will tests the following circumstances for each launcher.

1. We will always run torch_distributed test as the base case for torch distributed training. This is to ensure torchrun is always working.
2. When SMDDP is not available in our DLC, we will run test using pytorchddp launcher along with a training script that uses nccl backend. SMDDP tests with smdistributed launcher will be skipped. This is to ensure when SMDDP is not installed, running with mpirun run still works out of the box.
3. When SMDDP is available in our DLC, we will run test using smdistributed launcher with a different training script that uses smddp backend. pytorchddp tests will be skipped. This is to ensure that once SMDDP binary is installed, mpirun remain functional.

Tests run

• d05b668 PT 2.3 Passed SM EFA test
• 3f84983 PT 2.2 Passed SM EFA test
• 3a9c1f1 PT 2.1 Passed SM EFA test
• e2abb39 PT 1.13 Passed SM EFA test

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"

• I have run builds/tests on commit for my changes.

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 </path/to/buildspec.yml> -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 </path/to/buildspec.yml> -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:

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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

• I have run 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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Fill out the template and click the checkbox of the builds you'd like to execute

Note: Replace with <X.Y> with the major.minor framework version (i.e. 2.2) you would like to start.

• build_pytorch_training_<X.Y>_sm

• build_pytorch_training_<X.Y>_ec2

• build_pytorch_inference_<X.Y>_sm

• build_pytorch_inference_<X.Y>_ec2

• build_pytorch_inference_<X.Y>_graviton

• build_tensorflow_training_<X.Y>_sm

• build_tensorflow_training_<X.Y>_ec2

• build_tensorflow_inference_<X.Y>_sm

• build_tensorflow_inference_<X.Y>_ec2

• build_tensorflow_inference_<X.Y>_graviton

Additional context

PR Checklist

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• 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.
• (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

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• (If applicable) I have added the marker @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)
• (If applicable) I have added the marker @pytest.mark.integration("<feature-being-tested>") 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(<integer-num-nodes>) 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.

[ruhanprasad]

Approved, just had one minor comment