GitLab

* rm batch_dim, sequence_dim, sequence_parallel_output
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* rm lhs_quantized_colwise and rhs_quantized_colwise
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* rm unnecessary transpose_batch_sequence arg from some modules
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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
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* 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
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* fixed linting issues
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* added assert on sequence-parallel options when GemmPrimitive is disabled
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* added XLA FFI custom op for TE/common nvte_cublas_gemm
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started GemmPrimitive, abstract done
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gemm custom op working with BF16, needs testing for FP8/MXFP8
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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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* TensorUsage + FP8 GEMM with all layouts handling on BW
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---------
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* Support MXFP8 and handle empty matrices
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---------
Signed-off-by: Hua Huang <huah@nvidia.com>

* 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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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>
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* Implemented GroupedDense and TestGroupedDense for BF16, FP16, and FP8 
* Fix GroupedGemmFFI cuBLAS workspace alignment bug
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---------
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Revert "[JAX] GroupedDense v.2 without dynamic shape (#1721)"

This reverts commit 5d01ef21

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

* Implemented GroupedDense and TestGroupedDense for BF16, FP16, and FP8 
* Fix GroupedGemmFFI cuBLAS workspace alignment bug
Signed-off-by: Hua Huang <huah@nvidia.com>
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* [JAX] Update flax module param initialization to support logical partitioning axes
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Fix ffn1 intermediate result being replicated
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* Lint
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* Add documentation and assert when logical_axes=None
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* Fix bias in LayerNormMLP flax module
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* Fix layer tests to not use nn_partitioning and instead use nn.with_logical_axes
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---------
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* exclude GroupedGemm APIs
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---------
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* 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

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

* 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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Co-authored-by: Hua Huang <huah@nvidia.com>
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