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* adding more stuff missing from cherry picky jeremy PR for inspecting
Signed-off-by: tdophung <tdophung@nvidia.com>

* fix some tracing issues when intergating to maxtext
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* Have sort_chunks_by_index handle situations where input buffer is larger than num tokens
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* remove unnecessary assert and comments
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* remove Jeremy's PR for inspect ffi
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* untouch the amax file, also change comment on te
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return tokens_per_experts always
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* initial impl, not tested
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* consolidate different unpermute primitives with with_pad and with_merging_probs booleans. Implement partitioning for all permutation primitives
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* Add distributed test for non-padding permutation
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* fix issues in distributed test for padding permutation. Make common kernel zero intiialize output permuted scales, permuted probs and output tokens
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* revert zeroing in triton common kernel as it is a race condition. Instead, add extra input (aliased wiuth output) buffer to inner primitive of permutation on jax side to pass in zero intitiated buffers done with jnp zeros
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* fix utils to handle input output aliasing in autotuned kernels
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* Clean up comments, and add more comments explaining input output alias in utils
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* fix lint and greptile comment
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* fix issues that lint fixing introduced
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Update copyright to include 2026
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* [PyTorch] Fuse permute+pad and unpermute+unpad ops for FP8 optimization

1.Fused `moe_permute_with_probs` + `Fp8Padding` and fused `moe_unpermute` + `Fp8Unpadding`,
  that can remove the explicit padding/unpadding of moe expert, improved performance and reduced peak gpu memory usage.
2.Add tests of fused permute/pad and unpermute/unpad.
Signed-off-by: xiaoxi-wangfj <690912414@qq.com>

* [PyTorch/Common] Fuse permute+pad and unpermute+unpad support with_merging_probs
Signed-off-by: xiaoxi-wangfj <690912414@qq.com>

* [PyTorch]format code
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* [Common]perf expert_idx loaded once
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* fix: pad_offsets can be None
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
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* add padding + merging probs bwd support. Not tested
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* Fix garbage initialized act grad
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* all test passing for jax permutation + pad
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* change tokens_per_experts APIs to num_out_tokens with conservative allocation of worst case padding for output buffer
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* change test permutation to reduce test time
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* triggering PR refresh
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* format code
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* Remove some tests cases from pytorch side. Add a separate toekn_dispatch test for sanity in case combine accidentally undo an error on dispatch in the roundtrip test. Add distinction between L0 and L2 in test cases in jax
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* format code
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* remove chance for inefficiency in moving between CPU and GPU, remove redundant primitive using a new static bool for padding, add assert for align size
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* fix lint in jax
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* account for both jax newer and older than version 0.8.2. Adjusted gpu triton binding accordingly
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* format code
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* fix typo
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Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Co-authored-by: tdophung <tdophung@nvidia.com>

* branch off of initial permutation jax-triton PR
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* Set 0 as the size of dummy tensors to reduce memory usage.
Signed-off-by: tdophung <tdophung@nvidia.com>

* Correct setting of permuted_probs_stride_token, unpermuted_probs_stride_token and unpermuted_probs_stride_expert in unpermutation
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* Implement primitives, wrapper, test for wrapper, edit trit
on binding to accomodate scalars
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* Change implemementation of VJP functions to match correct pattern. Deduce some static scalar args from shapes of inputs. Accept B, S instead of num_tokens. Change test to use value_and_grad to test vjp funcs properly
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* formatting
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* fix pylint
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* fix test to compare to the correct reference impl. relax 1 tol for grad compare, fix lint the rightway
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* fix test_permutation to use value_and_grad for reference impl, tighten tols, and add unpermute with probs for token combine bwd rule
Signed-off-by: tdophung <tdophung@nvidia.com>

* added forgotten file in prev commit
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* format
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* merge with_probs to without_probs
Signed-off-by: tdophung <tdophung@nvidia.com>

* add aserts and fix lint
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Signed-off-by: tdophung <tdophung@nvidia.com>
Co-authored-by: Ming Huang <mingh@nvidia.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>