[tensorflow, pytorch][build][sagemaker] Updated smdataparallel binary to support EFA

[karan6181]

• Updated smdataparallel binary to support EFA

Issue #, if available:

PR Checklist

• I've prepended PR tag with frameworks/job this applies to : [mxnet, tensorflow, pytorch] | [ei/neuron] | [build] | [test] | [benchmark] | [ec2, ecs, eks, sagemaker]
• (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.

Pytest Marker Checklist

• (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

EIA/NEURON Checklist

• When creating a PR:

• I've modified src/config/build_config.py in my PR branch by setting ENABLE_EI_MODE = True or ENABLE_NEURON_MODE = True

• When PR is reviewed and ready to be merged:

• I've reverted the code change on the config file mentioned above

Benchmark Checklist

• When creating a PR:

• I've modified src/config/test_config.py in my PR branch by setting ENABLE_BENCHMARK_DEV_MODE = True

• When PR is reviewed and ready to be merged:

• I've reverted the code change on the config file mentioned above

Reviewer Checklist

• For reviewer, before merging, please cross-check:

• I've verified the code change on the config file mentioned above has already been reverted

Description:

Tests run:

DLC image/dockerfile:

Additional context:

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.

[jeet4320]

TF2 is failing due to capacity issue

E sagemaker.exceptions.UnexpectedStatusException: Error for Training job test-tf-smdataparallel-1619652004-96b6: Failed. Reason: CapacityError: Unable to provision requested ML compute capacity. Please retry using a different ML instance type.

[jeet4320]

All Pytorch tests are passing on first commit of this PR.

[jeet4320]

All TF2 tests are green as well

[karan6181]

All TF2 tests are green as well

Is the TF1 CI hanged?

[jeet4320]

I have cancelled those as those are not needed and they unnecessary take instance capacity

[jeet4320]

Will merge PR today as all needed tests are passing