update the param_id calculation so that it works on both CPX and SPX modes#271
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update the param_id calculation so that it works on both CPX and SPX modes#271amd-sriram merged 1 commit intomasterfrom
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update the param_id calculation so that it works on both CPX and SPX modes - ROCm/apex#271
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! cherry-pick release/1.8.0 |
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Commit Messages: - update the param_id calculation so that it works on both CPX and SPX modes (#271) PRs: - ROCm/apex#271 Fixes: - https://example.com/issue-271
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update the param_id calculation so that it works on both CPX and SPX modes - ROCm/apex#271 Fixes : https://ontrack-internal.amd.com/browse/SWDEV-548434
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update the param_id calculation so that it works on both CPX and SPX modes
Motivation
These 4 tests failed in MI308 machine because they had virtual GPUs
Technical Details
On CPX, local device ids are not laid out in contiguous DP groups. So the computed param_id doesn’t match the stage that initialized the module
So the solution is to use
param_id = parallel_state.get_pipeline_model_parallel_rank() + vm_id * pipeline_model_parallel_world_sizeTest Plan
The indivigual tests were tested with this
`python3 tests/L0/run_transformer/test_pipeline_parallel_fwd_bwd.py -k test_learning_async_pipelining_with_interleaving
`python3 tests/L0/run_transformer/test_pipeline_parallel_fwd_bwd.py -k test_learning_async_pipelining_without_interleaving
`python3 tests/L0/run_transformer/test_pipeline_parallel_fwd_bwd.py -k test_learning_pipelining_with_interleaving
python3 tests/L0/run_transformer/test_pipeline_parallel_fwd_bwd.py -k test_learning_pipelining_without_interleavingAnd all the test were tested with this.
python3 run_test.py --include run_transformerTest Result
Tested with this docker
registry-sc-harbor.amd.com/framework/compute-rocm-rel-7.0:24_ubuntu22.04_py3.10_pytorch_lw_rocm7.0_internal_testing_d36b5258
Attached log file
Run_Transformer_test.txt
Fixes : https://ontrack-internal.amd.com/browse/SWDEV-548434