[perf]Support MOE Multi-stream in Deepseek #947
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David9857
changed the title
Signed-off-by: David9857 <985700846@qq.com>
Signed-off-by: David9857 <985700846@qq.com>
wangxiyuan
reviewed
May 29, 2025
| global_bs = 0 | ||
| moe_expert_num = len(expert_map) | ||
| # hidden_states = hidden_states.bfloat16() | ||
| kwargs = { | ||
| kwargs1 = { |
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rename to a readable name
vllm_ascend/envs.py
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| @@ -36,6 +36,8 @@ | |||
| lambda: bool(int(os.getenv("COMPILE_CUSTOM_KERNELS", "1"))), | |||
| "VLLM_ENABLE_MC2": | |||
| lambda: bool(int(os.getenv("VLLM_ENABLE_MC2", '0'))), | |||
| "VLLM_ENABLE_CV_PARALLEL": | |||
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use additional_config instead of env, since this change is only used for torchair GE mode. like #839 does, there are another 3 new config option coming.
how about
{
"additional_config": {
"torchair_graph_config": {
"enable": True,
"enable_cv_parallet": True,
"batch_sizes": "12345",
"batch_sizes_init": True
}
}
}
cc @zzzzwwjj
|
And don't forget add e2e test. The model weight is here: https://www.modelscope.cn/models/vllm-ascend/DeepSeek-V2-Lite-W8A8 take https://github.com/vllm-project/vllm-ascend/blob/main/tests/multicard/test_offline_inference_distributed.py#L49 as an example |
Signed-off-by: David9857 <985700846@qq.com>
Signed-off-by: David9857 <985700846@qq.com>
Signed-off-by: David9857 <985700846@qq.com>
Signed-off-by: David9857 <985700846@qq.com>
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What this PR does / why we need it?
Support MOE inner Multi-stream for Deepseek
Does this PR introduce any user-facing change?
How was this patch tested?