GitLab

Signed-off-by: Quentin Anthony <qganthony@yahoo.com>

This function is more accurate than torch.log() for small values of input - https://pytorch.org/docs/stable/generated/torch.log1p.html

Found with TorchFix https://github.com/pytorch-labs/torchfix/

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* add mask-based moe permutation

* change moe_chunk_permute to moe_sort_chunks_by_indices

* fix __all__ in pytorch/permutation.py

* fix func/var names and typos; update tols in UT

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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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only compare the recipe in AttentionParams.fp8_meta
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Consolidate the distributed fused attention tests to shared input generation and execition logic.
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* corrected RS overlap BF16 output clashing with Float8Tensor constructor
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* Add a compile option to compile activation kernels with fast math
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* Fix
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* support AG overlap in sequence-parallel Linear forward and RS overlap in sequence-parallel Linear backward
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* add test_multiprocessing_encoder with processing spawning in bash

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Take token count quantization of fused attention into consideration for CP results correction (#1396)

* fix second half lse shape
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Correct fused attention output after each step to reduce intermediate memory use.
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the current implementation would release the output of ln, leading to an error if setting `return_layernorm_output=True`.
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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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* Fix pylint
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* WIP: fix get_swa_mask for padding
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* fix lint
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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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* Add jax.jit, replace _token with segment_ids, rename bias shape enum
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* Remove cache for fa deterministic which causes UT failed
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add max_t for KV
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* draft implementation of fsdp2 fp8 all gather
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* softmax custom calls with correct encapsulates

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* Bug Fix: Use default factory for not sharing mutable default values
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* cuDNN normalization integration
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Debug Mcore integration test

Avoid FP8 on Ampere and older. Generate synthetic data instead of depending on external data.
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* always have padding mask type for both flash and fused attentions
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Debug jobs to deploy nightly docs
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