Implement DDP static_graph=True
#6940
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Experimental implementation of new PyTorch 1.11.0 DDP feature.
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Profiling results 0.206 (PR) vs 0.209 hours (master). Should repeat. |
tdhooghe
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Jun 10, 2022
* Implement DDP `static_graph=True` Experimental implementation of new PyTorch 1.11.0 DDP feature. * Add 1.11.0 check * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
ctjanuhowski
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Sep 8, 2022
* Implement DDP `static_graph=True` Experimental implementation of new PyTorch 1.11.0 DDP feature. * Add 1.11.0 check * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Experimental implementation of new PyTorch 1.11.0 DDP feature. See https://pytorch.org/blog/pytorch-1.11-released/ for details.
🛠️ PR Summary
Made with ❤️ by Ultralytics Actions
🌟 Summary
Enhanced PyTorch compatibility and optimized model training performance in multi-GPU setups.
📊 Key Changes
check_versionutility function to confirm PyTorch version compatibility.static_graphparameter in DDP based on PyTorch version check.🎯 Purpose & Impact
check_versionfunction ensures the training script is compatible with specific PyTorch versions; this prevents potential version-related errors for users.static_graph=Truewithtorch.nn.parallel.DistributedDataParallel(DDP) when available (PyTorch 1.11.0+) optimizes performance during training with static computational graphs, leading to potentially faster and more efficient multi-GPU training.