GitLab

* Delete row-wise data in single-GPU linear forward
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug Python->C++ parsing of transpose-only Float8Tensors
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* Debug tensor shape calculation without row-wise data
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* Debug correctness issues with only column-wise data
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* Only cache column-wise input in LayerNormLinear
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* Support MXFP8 all-gather with only column-wise data
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* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Fix moe cases, lint, rm unused ctx
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* Fix CPU activation offloading and use consistent logic for save/restore
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* Fix tests
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* Fix typo
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* RM stray file
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* Fix distributed and cpp tests
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* Fix norm cpp tests
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* Rm stray file
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* RM stray file
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* Fix MXFP8 AG
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* Fix FP8 with sequence parallelism
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* Fix UB bulk dgrad
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* Verified TE2.0 with offloading
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* Skipping tests for Ampere and removed child class preparing
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* offloading support for MXFP8 dtype
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* Changed quantized tensor detection mechanism
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* Fix mxfp8 offload, lint errors, and var name
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* Supported disabling offloading for quantized tensors
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* bug fix
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* Fixed bugs
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* Added support for None in list of Quantized data tensors
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* Hopper backward compatibility cleanup
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* Coding style nit
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* Added guards
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* Fix issues for MCore DDP.
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* Remove force data release for CPU offloading.
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* Add preserved attributeds.
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* Add main_grad to prevserved attributes.
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* Change prepare_for_saving to original tensor and add .data to CPU hook.
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* Update.
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* Fix for LayernormLinear in FP8.
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* Upgrade pylint and first round formatting
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* Format and fixes
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* Paddle lint
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* Reviews
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* FIxes
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* More linting
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* Run formatter
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* Paddle lint
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* Fixes
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---------
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* CPU perf optimization in linear autograd function

Avoid enable_grad context when possible in cast function. Cache distributed group properties.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* CPU perf optimization in prepare_forward function

Avoid torch.nn.Module impl of __setattr__.
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* Avoid module import in TE module forwards
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* Use fast getter for params
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* Reuse tensor dims in linear autograd func
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* Apply optimizations to grouped linear
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug test failures
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* Debug test failures
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* Fix linter warnings
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* Avoid deepcopy in tests
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* Move _fast_setattr logic to __setattr__ method
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* Load balanced offloading algorithm
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* removed unwanted memcpyDtoD/fixed weight parametrisation
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* Apply formatting
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* Apply formatting
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* Remove unnecessary Pylint overrides
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* Fixes to lint
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Fixed offloading for PyT version/ Added Attention activation offloading support/ Native FP8 support (#632)

* Fixed offloading for PyT version/ Added Attention activation offloading support/ Native FP8 support
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* Removed activation offloading for fused attention
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* Fixed the illegal memory access issue for activation offloading of attention
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* Removed the version guard
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* Pipeline failures fix
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* Fixed lint erros
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* Lint error fix
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Activation offloading to CPU's for the Linear, Layernorm Linear and the Layernorm MLP modules (#571)

* Added support activation offloading to CPU's
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* Moving CPU offloading library to TE
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* Restructured code, added switch to choose between weight/activation offloading
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* Removed arg during constructor
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* Fix nit-pick errors
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* Documentation fixes
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* Fix to the code block in docs
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* Added offloading unit test
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* Fixed formatting
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* wgrad fusion fix, minor errors and lint
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* Errors, test, lint
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* RM test file
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* Fixed stray PyT tensors in LayernormMLP getting offloaded
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* Fixed typi
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* Fix offloading for rmsnorm, rm test
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* Fix errors
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* Float8Tensor compatible offloading
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* Cleanup
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