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[Inference] Add multi-block mmha in FusedMT. by Wanglongzhi2001 · Pull Request #67211 · PaddlePaddle/Paddle · GitHub
Wanglongzhi2001
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[WIP] fmha support flash decoding
[Inference] fmha support flash decoding
Aug 8, 2024
Wanglongzhi2001
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[Inference] fmha support flash decoding
[Inference] Add multi-block mmha in FusedMT.
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[Inference] Add multi-block mmha in FusedMT. #67211
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你的PR提交成功，感谢你对开源项目的贡献! |
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| // 1.f / sqrt(Dh) | ||
| float inv_sqrt_dh; | ||
| float inv_compression_ratio = 1.0f; |
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直接加上rope embedding的话这些参数是否还要保留呢?
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Done.
| *reinterpret_cast<Vec*>(&src_vec) = src; | ||
| #pragma unroll | ||
| for (int i = 0; i < VecSize; i++) { | ||
| src_vec[i] = src_vec[i] * static_cast<T>(scale); |
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这个是否先需要用float32计算再cast成T存储?
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Done.
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这个会有啥影响吗？
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这个会有啥影响吗？
精度问题，scale 是 float 类型的，先向下 cast 成 T 类型再计算可能会掉精度。
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yuanlehome
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Aurelius84
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LGTM for flags
raindrops2sea
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sneaxiy
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PR Category
Inference
PR Types
New features
Description
pcard-71500
支持 FusedMT 中的 mmha 的 128K 上下文推理，开发了 multiblock 的 mmha kernel，期间使用 flash decoding 算法进行 head 的分块。
[NOTE]
单测里的上下文长度设置为 128K 可能导致单测耗时太长挂掉，因此单测的上下文长度仅设置成 2049 以及 layers 仅设置成 2 层。
[使用方式]
使用
export FLAGS_fused_multi_transformer_op_use_mbfmha =true打开 FLAGS_fused_multi_transformer_op_use_mbfmha 后就行，无需额外操作，后续步骤和使用 FusedMT 的步骤一致。