GitLab

Remove xla_ignore_channel_id check and ignore Scan loop warning in unit test
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix wheel install after src install
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* Fix JAX imports
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* Fix lint
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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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flax module with compute dtype inferred from the inputs
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Fix issues when mask/sequence_descriptor is None
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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

* add init_dtype as an optional arg to all modules

* update use_scan query from xla flags

* relax threshold for test_encoder fp8

* relax the tols

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* POC for segment_ids/segment_pos
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* Change segment_pos position
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* Use RemainingArgs to solve number of parameters mismatches
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* Test mask_descriptor for accomendating different mask representations
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* Fix bugs
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* Use descriptor in bwd
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* segment_ids/pos support POC
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* Move seqlens/offsets generation to mask descriptor
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* Rename MaskDescriptor to SequenceDescriptor
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* Generalize get_seqlens_and_offsets
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* Migrate to new API
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* Remove small inputs and test different input format
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* Fix lint
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* Fix seed shardings
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Consolidate the distributed fused attention tests to shared input generation and execition logic.
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Correct fused attention output after each step to reduce intermediate memory use.
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* Fix SWA mask for THD and forcing seqlen_kv >= seqlen_q for SWA
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* Generalize sliding window mask
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* final fixes
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* upgrade to FE 1.9-rc
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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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* Fix THD cross reference code
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* Remove explicit segment_pad, encoding it to segment_ids
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* Remove cache for fa deterministic which causes UT failed
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* Rename fixture to avoid conflict
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Scale sequence length in CP tests to avoid tiny sizes.
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* Implement ring attention primative for Jax.
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* FFI for some transpose & activation functions
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* Remove comments in transformer_engine/jax/csrc/extensions/activation.cpp
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Exposed context parallel params to DPA api
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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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* Bug fix for FFI data type mismatch

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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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Add THD + GQA supports for cuDNN >= 9.6
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Update test to check support for context parallel attention.
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* Expose JAX sliding window attn API
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* No SWA in context parallel; fix RNG seed in test
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* Update test_praxis_layers.py for SWA, test passed
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* Use tuple window_size; update for PR #1212
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* Add and adjust some pytest.skip
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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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* Add enabled() to BasePrimitive

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Cleanup
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