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* check in per-tensor current scaling full recipe
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setup basics of current scaling quantizer in python level
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add test case for current scaling dequantize
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achieved zero tolerance for Linear by specify gemm use_split_accumulator config
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enable layernormlinear with current scaling, pass bitwise test
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make current scaling quantizers distrbuted, pass distributed linear&layernormlinear tests
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bug fix: use cached fp8 recipe in backward
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fix layernorm_mlp with current scaling, fix activation_helper with current scaling
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support detailed numerical settings from recipe to quantization kernel
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resolving MR comments
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* add current scaling to test_numerics.py, skip act recomp and grouped linear
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* add benchmark for quantizer
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* resolve mr comments, fix activation cast fusion
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* resolve comments, add NVTEQuantizationParams for compute scale
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* Remove current scaling mode from core lib
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* Refactor current-scaling-specific logic in core C++ lib

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* cuDNN normalization integration
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* [TE/PyTorch][MoE] Add FP8 padding and unpadding module 

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rm test_dgeglu
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* Fix 2
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