fix no_shard training convergency and add unittest for no_shard - #3754
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add unittest for no_shard and add empty cache to avoid OOM add meta_device_check for no_shard following fully_shard.py:326 Signed-off-by: jinliangl <jinliangl@nvidia.com>
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/ok to test 153b1f8 |
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# Description NVIDIA#4024 NVIDIA#3746 NVIDIA#2799 NVIDIA#3676 NVIDIA#4133 NVIDIA#3295 NVIDIA#3831 NVIDIA#3754 ## Type of change - [ ] New feature (non-breaking change which adds functionality) - [ ] Infra/Build change (changes to CI/CD workflows or build scripts) - [ ] Code refactoring - [ ] Documentation change - [x] Bug fix - [ ] Breaking change ## Changes - Content 1 - Content 2 - Content 3 - Content 4 ## Checklist - [ ] I have read and followed the contributing guidelines - [ ] The functionality is complete - [ ] I have commented my code, particularly in coverage report uploading steps - [ ] I have made corresponding changes to the documentation - [ ] My changes generate no new warnings - [ ] I have added/updated tests that prove my feature works - [ ] New and existing unit tests pass locally --------- Signed-off-by: Cory Ye <cye@nvidia.com> Signed-off-by: yexiaochuan <yexiaochuan@baidu.com> Signed-off-by: Akshat Kumar <akshat230405@gmail.com> Signed-off-by: Youngeun Kwon <youngeunk@nvidia.com> Signed-off-by: jinliangl <jinliangl@nvidia.com> Co-authored-by: Ritesh Patel <ripatel@nvidia.com> Co-authored-by: Cory Ye <cye@nvidia.com> Co-authored-by: Cory Ye <44509866+cspades@users.noreply.github.com> Co-authored-by: Xiaochuan Ye <tap91624@gmail.com> Co-authored-by: yexiaochuan <yexiaochuan@baidu.com> Co-authored-by: Akshat8510 <akshat230405@gmail.com> Co-authored-by: Kunlun Li <94586211+kunlunl@users.noreply.github.com> Co-authored-by: eternally-z <zzywzj@gmail.com> Co-authored-by: Philip Petrakian <ppetrakian@nvidia.com> Co-authored-by: Youngeun Kwon <youngeunk@nvidia.com> Co-authored-by: xuwchen <xuwenc@nvidia.com> Co-authored-by: Li Jinliang <jinliangl@nvidia.com>
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What does this PR do ?
Fixes no_shard convergence by correcting grad_norm and all_reduce logic.
init_model_with_meta_devicefollow fully_shard.py:326Grad_norm and loss convergency and unittest result is below.
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