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Revert "[JAX] Disable TE Norm Custom Calls (#1993)"

This reverts commit 6c970612

.

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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

Disable Norm custom calls
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* new gemm operand specs processing
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* fix for lhs_non_specs
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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[JAX] Fixing GemmPrimitive partitioning rules to handle tensor-parallelism correctly for sequence-parallel inputs (#1980)

* updated GemmPrimitive partitioning rules to explicitly control all-reduce vs. reduce-scatter for sequence-parallelism
Signed-off-by: Alp Dener <adener@nvidia.com>

* corrected handling of FSDP sharding for the RHS operand
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* use correct logical axes variable to identify sequence-parallel dim in LayerNormDenseGeneral
Signed-off-by: Alp Dener <adener@nvidia.com>

* fixed linting issues
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* added assert on sequence-parallel options when GemmPrimitive is disabled
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* add manage_primitives() helper

* disable GEMM primitives for non-MXFP8 recipes

* implement the NVTE_JAX_CUSTOM_CALLS + deprecate NVTE_JAX_CUSTOM_CALLS_RE

* replace NVTE_JAX_CUSTOM_CALLS_RE with NVTE_JAX_CUSTOM_CALLS in TE tests and examples

* fix use_jax_gemm contextmanager
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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* remove unnecessary padding
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* adapt the test_distributed_layernorm byte count
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* added XLA FFI custom op for TE/common nvte_cublas_gemm
Signed-off-by: Alp Dener <adener@nvidia.com>

started GemmPrimitive, abstract done
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gemm custom op working with BF16, needs testing for FP8/MXFP8
Signed-off-by: Alp Dener <adener@nvidia.com>

converted TE GEMM API to use ScaledTensor and added os ENV flag to use TE GEMM under general gemm() call
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BF16 tests passing, FP8 tests should be passing but contracting_dims has a scoping issue
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fp8 tests passing for E4M3, getting CUBLAS_STATUS_NOT_SUPPORTED for E5M2
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updated GEMM API to use separate LHS and RHS quantizers instead of a QuantizerSet
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new GemmPrimitive passing all Dense tests
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import cleanup and reverted code chunk movement
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removed unused .transpose() implementations from ScaledTensors
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all custom call tests passing on Hopper, GEMM-related tests cover both GemmPrimitive and native JAX impl
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removed direct calls to GemmPrimitive.enabled() from outside of cpp_extensions
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removed unused changes to ScaledTensor classes and debug prints
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* minor unit test cleanup
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* FP8 tests passing on Blackwell but MXFP8 outputs NaN
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* reverted dense and fuseddense changes, FP8 test passing on Hopper and Blackwell, MXFP8 has issues with E5M2
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* MXFP8 issue traced to scale factor padding with NaNs instead of zeros
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* padding scale with 2^-127 instead of nans
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* fix bug on rhs_scale_inv usage
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* cleanup E8M0 type converter use it in gemm.cpp
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* segfault fixed, passing all unittests on Blackwell
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* fix for fuseddense tests
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* fix workspace alignment
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* fixed GemmPrimitive custom partitioning to match jax.nn.scaled_matmul
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all unit tests passing on H100x8 node
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linting fixes
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fixed batch dimension numbers
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fixed FP8 scale sharding rule when there are no FP8 scales
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added error message for unsupported Shardy partitioner
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fixed test tolerances for FP8 cases
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fixed shardy test skip cases
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* moved reshape of encoder output in encoder examples to make custom partitioning rules work correctly
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* added helper functions for padding and unpadding block scales, changed GemmPrimitive to accept unpadded scales and pad them after sharding
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* updated shardy rules for all custom ops to decouple block scale rules from their tensors
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* fixed linting errors
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* changed unit test use_jax_gemm option to be a context to preserve external custom op settings, tightened multi-GPU encoder test tolerances, changed gemm() API to use contracting_dims and batched_dims separately instead of dimension_numbers
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* fixed typo in test utils
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* added sequence-first input warnings
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* fixed datasets version for JAX examples
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* reverting modification to force_1x_quantization decision
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* corrected gemm function syntax in unit tests
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* Fix JAX grouped gemm error on CUDA 12.9.1 & later by using 16B alignment for scale ptr
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* Pad MXFP8 scales with 2*-127 instead of NaNs
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* TensorUsage + FP8 GEMM with all layouts handling on BW
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* Support MXFP8 and handle empty matrices
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* Add support for Fused Attn MLA head_dim_qk != head_dim_v
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	Modify DotProductAttention call() to extract head dims separately for qk and v
	Modify the FusedAttn Tests to accommodate for API changes in FusedAttn API
	Add test case for head_dim_qk != head_dim_v (failing)
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* Fix context dims in general DPA in test_fused_attn
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* Use new FusedAttnRunner function signature for separate hidden dim for qk and v in Fused Attn distributed tests
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* Fix usage of is_fused_attn signature in distributed tests
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* Remove unnecessary assert
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* add support for head dim > 128
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* bump sm100 to sm100+
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* enable sq=1 for bprop
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* minor tweak in comments
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* fix head_dim logic and remove pytest skip
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* fixes for jittable grouped_quantize

* fixes for jittable grouped_gemm

* fix contracting_dim for wgrad gemm

* exclude jitted grouped_gemm from the unit test as it does not work cudaGraph

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* Implemented GroupedDense and TestGroupedDense for BF16, FP16, and FP8 
* Fix GroupedGemmFFI cuBLAS workspace alignment bug
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Revert "[JAX] GroupedDense v.2 without dynamic shape (#1721)"

This reverts commit 5d01ef21

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* Implemented GroupedDense and TestGroupedDense for BF16, FP16, and FP8 
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* refactor the multi_stream utils + implement nvte_multi_tensor_quantize in TE/Common

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* fix logical_axes_names for transpose tensor in ScaledTensor
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* fix otype for fp8 gemm
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* Fix 1x quantize kernel availability check on hopper

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* Use 1x quantization + jax transpose on BW for performance
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* Use 1x quantization on Hopper as well as it is also faster
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* Undo architecture check helper function
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* Lint
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* Support SWA in CP Ring Attn THD striped sharding
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* Add some comments; move check to _FusedAttnCPWithP2PHelper.check_supported()
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Remove unused check
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* removes unnecessary reshapes for FP8 GEMM

* use nn.jax.scaled_matmul
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* fp8 gemm with direct quant
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Update jax_scaled_masked_softmax to match TE kernel implementation
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Make primitive names more granular for better disabling granularity
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This reverts commit 5bee81e2

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* removes unneccessary reshapes for FP8 GEMM

* use nn.jax.scaled_matmul
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* Enforce input sharding of norm primitive does not shard hidden dim
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* Fix partitioning issue in dact primitive causing NaN and add better shape checks before calling TE API
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* Move dact shape assertion from cpp to python
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* exclude GroupedGemm APIs
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Fix distributed layernorm test failure
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* [JAX-Q] Single GPU current scaling for JAX
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Check CuDNN version and apply unfused norm if
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* Add experimental Shardy support.

Production use is not yet recommended.

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* scaling enum abstract

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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* rm no scaling enum
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* update jax enum
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* rename QuantizeAxis to QuantizeLayout, get_layout to get_data_layout, q_axis to q_layout

* add fatten_axis option

* added gated act to test encoder

* sharding constraint fixes

* fix padding when flattening first dim needs to be padded

* update test sizes so that padding is tested

* rm output sharding as it can be done in the flax module

* sharding scale_inv for mxfp8

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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>