[Bugfix] rename enable_flash_comm_v1 back to enable_sp (#6883)
### What this PR does / why we need it?
PR #5632 introduced a bug by replacing some branches gated by enable_sp
with enable_flash_comm_v1. As a result, when enable_shared_expert_dp is
enabled alone (i.e., VLLM_ASCEND_ENABLE_FLASHCOMM1=0 and
VLLM_ASCEND_ENABLE_FLASHCOMM=0), the behavior becomes inconsistent with
the previous logic and leads to accuracy issues. This PR restores the
original enable_sp-based branching to recover expected behavior and
accuracy.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
#### 1. start server
``` bash
vllm serve /home/weights/DeepSeek-V2-Lite-W8A8/ \
--port 8001 \
--served-model-name auto \
--max-model-len 1024 \
--enforce-eager \
--tensor-parallel-size 2 \
--data-parallel-size 2 \
--gpu-memory-utilization 0.9 \
--enable-expert-parallel \
--additional-config '{"enable_shared_expert_dp": true}'
```
#### 2. curl
```bash
curl -s http://localhost:8001/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "auto",
"messages": [
{"role": "user", "content": "Hello. I have a question. Who are you?"}
],
"max_tokens": 10,
"temperature": 0.0,
"ignore_eos_token": true
}'
```
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
Signed-off-by: realliujiaxu <realliujiaxu@163.com>
This commit is contained in:
@@ -39,7 +39,6 @@ from vllm_ascend.utils import (
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COMPRESSED_TENSORS_METHOD,
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AscendDeviceType,
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check_kv_extra_config,
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enable_sp,
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flashcomm2_enable,
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get_ascend_device_type,
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is_moe_model,
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@@ -48,7 +47,7 @@ from vllm_ascend.utils import (
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update_aclgraph_sizes,
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update_cudagraph_capture_sizes,
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is_310p,
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enable_flash_comm_v1,
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enable_sp,
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)
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if TYPE_CHECKING:
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@@ -402,7 +401,7 @@ class NPUPlatform(Platform):
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)
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vllm_config.parallel_config.cp_kv_cache_interleave_size = cache_config.block_size
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if enable_flash_comm_v1():
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if enable_sp(vllm_config):
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assert not is_vl_model(vllm_config), """Flash Comm V1 is not supported for VL models. \
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Please disable it by setting VLLM_ASCEND_ENABLE_FLASHCOMM1=0. \
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For optimal performance with VL models, we recommend enabling Sequence Parallelism \
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