[PyTorch] Integration test for Megatron-LM#1329
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timmoon10 merged 7 commits intoNVIDIA:mainfrom Nov 21, 2024
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Signed-off-by: Tim Moon <tmoon@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
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Signed-off-by: Tim Moon <tmoon@nvidia.com>
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This was referenced Nov 13, 2024
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Pipeline 20444324 is green |
timmoon10
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Nov 20, 2024
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| if requires_grad != x.requires_grad: | ||
| if requires_grad: | ||
| x.requires_grad_() | ||
| else: | ||
| x = x.detach() |
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This fixes a te.Sequential bug that was exposed by Mcore. When running in eval mode, we want x.requires_grad=False so that the op knows that it doesn't need to prepare for that grad. However, PyTorch sometimes complains if you change a tensor's requires_grad from True to False (i.e. when the tensor is not a leaf in the autograd graph). Detaching the tensor works around this case.
sudhakarsingh27
approved these changes
Nov 20, 2024
| # Check tensor dims | ||
| weight = self.weight | ||
| weight_dims = tuple(weight.size()) | ||
| input_dims = tuple(input_.size()) |
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apparently torch.Size is a subclass of tuple so tuple creation probably not needed
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| # Check tensor dims | ||
| weight = self.weight | ||
| weight_dims = tuple(weight.size()) |
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no need to tupleize
Signed-off-by: Tim Moon <tmoon@nvidia.com>
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Nov 21, 2024
* Handle deprecated `hidden_size` arg in norm modules Signed-off-by: Tim Moon <tmoon@nvidia.com> * Support initializing norm ops on CPU Signed-off-by: Tim Moon <tmoon@nvidia.com> * Add integration test for Megatron-LM Signed-off-by: Tim Moon <tmoon@nvidia.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Rename Mcore integration test Signed-off-by: Tim Moon <tmoon@nvidia.com> * Handle case in RMSNorm where hidden dim is not provided Signed-off-by: Tim Moon <tmoon@nvidia.com> --------- Signed-off-by: Tim Moon <tmoon@nvidia.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Description
#1033 broke Megatron-LM's wrappers for the LayerNorm and RMSNorm modules:
hidden_sizearg tonormalized_shapein order to matchtorch.nn.LayerNorm, but Megatron-LM treatshidden_sizeas a kwarg:https://github.com/NVIDIA/Megatron-LM/blob/aded519cfb1de2abf96f36ca059f992294b7876f/megatron/core/extensions/transformer_engine.py#L65.
This PR adds logic to handle the
hidden_sizearg and print a deprecation warning.To help detect these issues in the future, I've also added an integration test that runs Megatron-LM to train a very small GPT model.
Type of change
Changes
hidden_sizearg in LayerNorm and RMSNorm modulesChecklist: