GitLab

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

* 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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* initialization with weight_dtype
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* fix a bug for at::from_blob with nullptr
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* fix a bug for non-TN
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* Updated docs for TE 2.0
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* Change from review
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* flax module to init params with given dtype
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* all tests passed
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* remove unneccessary reshape for kernel
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* Initial commit
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* Fixed compilation errors
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* Fixed pylint errors
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This function is more accurate than torch.log() for small values of input - https://pytorch.org/docs/stable/generated/torch.log1p.html

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* add mask-based moe permutation

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

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only compare the recipe in AttentionParams.fp8_meta
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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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Take token count quantization of fused attention into consideration for CP results correction (#1396)

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