Unified benchmark runner with YAML config #3259
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…rch#3251) Summary: - Moved the EBC-only logic into a separate file `benchmark_ebc.py` - Removed linter issues Differential Revision: D79512602
Summary: Added `benchmark_module` function that benchmarks the given module, sharding type, and planner across multiple GPUs. Differential Revision: D79515598
…lt (pytorch#3258) Summary: Stack pipeline benchmark per-rank-results into a single BenchmarkResult to measure overall performance across GPUs. This will cause 'intentional' **2x regression** for allocated memory metrics since we are accumulating the total memory stats across two given GPUs instead of measuring only one. After the change is landed, I will **re-register** the ServiceLab task with the new baseline metrics to avoid future false regression warnings. Differential Revision: D79537357
Summary: - Implemented unified benchmark runner with YAML configuration. - Created main benchmark executable unified_benchmark_runner.py. - Added example .YAML config files for both module and pipeline level benchmarks. Differential Revision: D79701597
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This pull request was exported from Phabricator. Differential Revision: D79701597 |
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Summary:
Differential Revision: D79701597