Add flash attention v2 and INT4 CUDA for LLaMA E2E benchmarking#20149
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onnxruntime/python/tools/transformers/models/llama/benchmark_e2e.py
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### Description This PR adds flash attention v2 and support for INT4 CUDA benchmarking in PyTorch. ### Motivation and Context The [flash attention v2](https://github.com/Dao-AILab/flash-attention) algorithm helps improve model performance in PyTorch. Support for INT4 CUDA in PyTorch is done through the [`bitsandbytes`](https://github.com/TimDettmers/bitsandbytes) package.
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…osoft#20149) ### Description This PR adds flash attention v2 and support for INT4 CUDA benchmarking in PyTorch. ### Motivation and Context The [flash attention v2](https://github.com/Dao-AILab/flash-attention) algorithm helps improve model performance in PyTorch. Support for INT4 CUDA in PyTorch is done through the [`bitsandbytes`](https://github.com/TimDettmers/bitsandbytes) package.
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Description
This PR adds flash attention v2 and support for INT4 CUDA benchmarking in PyTorch.
Motivation and Context
The flash attention v2 algorithm helps improve model performance in PyTorch. Support for INT4 CUDA in PyTorch is done through the
bitsandbytespackage.