GitLab

* refactor + mxfp8

* added grouped gemm

* rename linear to dense

* added cublas init phase for groupedGemm

* relax the tol of test encoder multiprocessing mxfp8 by 0.001
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* Fix softmax shape for THD format.
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Make ffi compatible with jax 0.4
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Remove xla_ignore_channel_id check and ignore Scan loop warning in unit test
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* Fix wheel install after src install
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* Fix JAX imports
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* switch order of dirs for finding so
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* Use existing dir src build
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* Fix lint
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---------
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* Support THD + ring attention for self attn
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* Consolidate reorder strategy
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* Fix dataclass frozen issue
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* Remove redundant code
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* Use AttnBiasType, AttnMaskType, QKVLayout in cpp_extension
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* Fix lint
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* Refine P2P helper check_supported
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* Add segment_ids/pos check
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* Fixup
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* Add dual chunk swap example
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* Align different reorder code structure
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---------
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* Expose THD to flex MHA module
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* Enhance docs
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* fixes L1 test

* fix test_multigpu_encoder

* fixes for other multi-encoder tests

* jax.extend.ffi to jax.ffi

* initialization with float32

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* update use_scan query from xla flags

* relax threshold for test_encoder fp8

* relax the tols

---------
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* flax module to init params with given dtype
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* all tests passed
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* remove unneccessary reshape for kernel
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* remove casting output of dot
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* clean up
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* Use RemainingArgs to solve number of parameters mismatches
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* Migrate to new API
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* Fix lint
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* Fix seed shardings
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* Optimize sequence converting overhead
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* Fix up
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* fix lint
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* Fix conflicts
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* Remove reduntant line
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Correct fused attention output after each step to reduce intermediate memory use.
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* Add util functions to attn_mask_type
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* Add util functions to qkv_layout
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* Remove cache for fa deterministic which causes UT failed
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* FFI for all softmax functions
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* FFI for FusedAttnBackward and Dequantize

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* Revert changes to tests/jax/test_fused_attn.py
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* Implement ring attention primative for Jax.
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* added prepare phase for the FusedAttnForwardFFI

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[JAX] XLA Custom Calls with FFI for FusedAttnFwd, Quantize, Transpose, ActLuFP8, LayerNormForwardFP8FFI, and LayerNormBackwardFFI (#1263)

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* Minor fix
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* Revise FusedAttnForwardFFI()
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* Add FFI_CudaGraph_Traits

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[JAX] Fix correctness of JAX fused attention with CP and improve numerics check in unit tests (#1282)

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fixed assertion bug for SWA
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* Revised following Reese Wang's comments

Still need further debugging:
FAILED test_fused_attn.py::TestFusedAttn::test_backward[NO_SWA-DROP_0.0-4-128-256-16-16-64-BF16-CROSS-KV_PACKED-NO_MASK-NO_BIAS] - AssertionError:
FAILED test_fused_attn.py::TestFusedAttn::test_backward[NO_SWA-DROP_0.0-4-128-256-16-16-64-BF16-CROSS-KV_PACKED-NO_MASK-POST_SCALE_BIAS-1HSS] - AssertionError:
FAILED test_fused_attn.py::TestFusedAttn::test_backward[NO_SWA-DROP_0.0-4-128-256-16-16-64-BF16-CROSS-SEPARATE-NO_MASK-NO_BIAS] - AssertionError:
FAILED test_fused_attn.py::TestFusedAttn::test_backward[NO_SWA-DROP_0.0-4-128-256-16-16-64-BF16-CROSS-SEPARATE-NO_MASK-POST_SCALE_BIAS-1HSS] - AssertionError:

These errors does not exist in the previous commit
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* Fix no-SWA test case errors in previous commit
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Implementation of context parallel fused attention using all-gather.
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