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flash-attention/csrc/ft_attention
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Tri Dao 2800efc71f [FT] rotary_cos/sin should have batch_size dimension
2023-07-06 15:33:33 -07:00
..
cuda_bf16_fallbacks.cuh [Gen] Add kernel from FasterTransformer for benchmarking 2023-01-03 17:37:43 -08:00
cuda_bf16_wrapper.h [Gen] Add kernel from FasterTransformer for benchmarking 2023-01-03 17:37:43 -08:00
decoder_masked_multihead_attention_template.hpp [FT] rotary_cos/sin should have batch_size dimension 2023-07-06 15:33:33 -07:00
decoder_masked_multihead_attention_utils.h [FT] rotary_cos/sin should have shape (dim) instead of (seqlen, dim) 2023-07-03 09:41:04 -07:00
decoder_masked_multihead_attention.cu [Rotary] Make sure frequency calculation is in fp32 2023-07-02 16:39:39 -07:00
decoder_masked_multihead_attention.h [Rotary] Make sure frequency calculation is in fp32 2023-07-02 16:39:39 -07:00
ft_attention.cpp [FT] rotary_cos/sin should have batch_size dimension 2023-07-06 15:33:33 -07:00
README.md [Gen] Add kernel from FasterTransformer for benchmarking 2023-01-03 17:37:43 -08:00
setup.py Support H100 for other CUDA extensions 2023-03-15 16:59:27 -07:00

README.md

Attention kernel from FasterTransformer

This CUDA extension wraps the single-query attention kernel from FasterTransformer v5.2.1 for benchmarking purpose.

cd csrc/ft_attention && pip install .