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Remove VLLM_USE_V1 (#4086)

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Drop VLLM_USE_V1 usage.  This env has been removed from vLLM already.

- vLLM version: v0.11.0
- vLLM main:
83f478bb19

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2025-11-11 15:43:39 +08:00
committed by GitHub
parent d5567680a2
commit f811a24bf0
21 changed files with 7 additions and 63 deletions
Download Patch File Download Diff File Expand all files Collapse all files

5
.github/workflows/nightly_benchmarks.yaml vendored
View File

@@ -46,14 +46,13 @@ jobs:
test:
if: ${{ contains(github.event.pull_request.labels.*.name, 'performance-test') && contains(github.event.pull_request.labels.*.name, 'ready-for-test') || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch' }}
name: Benchmarks/vLLM=${{ matrix.vllm_branch }}, vLLM-Ascend=${{ matrix.vllm_ascend_branch }}, use_v1=${{ matrix.vllm_use_v1 }}
name: Benchmarks/vLLM=${{ matrix.vllm_branch }}, vLLM-Ascend=${{ matrix.vllm_ascend_branch }}
runs-on: 'linux-arm64-npu-static-8'
strategy:
matrix:
include:
- vllm_branch: v0.11.0
vllm_ascend_branch: main
vllm_use_v1: 1
max-parallel: 1
container:
image: swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/cann:8.3.rc1-910b-ubuntu22.04-py3.11
@@ -73,7 +72,6 @@ jobs:
VLLM_USE_MODELSCOPE: True
ES_OM_DOMAIN: ${{ secrets.ES_OM_DOMAIN }}
ES_OM_AUTHORIZATION: ${{ secrets.ES_OM_AUTHORIZATION }}
VLLM_USE_V1: ${{ matrix.vllm_use_v1 }}
steps:
- name: Check npu and CANN info
run: |
@@ -200,7 +198,6 @@ jobs:
--created_at "$commit_time_no_tz" \
--res_dir ./benchmarks/results \
--error "$ERROR_MSG" \
--extra_feat '{"VLLM_USE_V1": "${{ matrix.vllm_use_v1 }}"}'
rm -rf ./benchmarks/results
cd -
done < commit_log.txt

1
docs/source/tutorials/multi_node.md
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@@ -160,7 +160,6 @@ export TP_SOCKET_IFNAME=$nic_name
export HCCL_SOCKET_IFNAME=$nic_name
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
vllm serve vllm-ascend/DeepSeek-V3.1-W8A8 \

2
docs/source/tutorials/multi_node_kimi.md
View File

@@ -70,7 +70,6 @@ export TP_SOCKET_IFNAME=$nic_name
export HCCL_SOCKET_IFNAME=$nic_name
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
# The w8a8 weight can be obtained from https://www.modelscope.cn/models/vllm-ascend/Kimi-K2-Instruct-W8A8
@@ -116,7 +115,6 @@ export TP_SOCKET_IFNAME=$nic_name
export HCCL_SOCKET_IFNAME=$nic_name
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
vllm serve /home/cache/weights/Kimi-K2-Instruct-W8A8 \

3
docs/source/tutorials/multi_node_pd_disaggregation_llmdatadist.md
View File

@@ -104,7 +104,6 @@ export HCCL_SOCKET_IFNAME="eth0"
export DISAGGREGATED_PREFILL_RANK_TABLE_PATH="/path/to/your/generated/ranktable.json"
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
export VLLM_USE_V1=1
vllm serve /model/Qwen3-30B-A3B \
--host 0.0.0.0 \
@@ -144,7 +143,6 @@ export HCCL_SOCKET_IFNAME="eth0"
export DISAGGREGATED_PREFILL_RANK_TABLE_PATH="/path/to/your/generated/ranktable.json"
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
export VLLM_USE_V1=1
vllm serve /model/Qwen3-30B-A3B \
--host 0.0.0.0 \
@@ -183,7 +181,6 @@ export HCCL_SOCKET_IFNAME="eth0"
export DISAGGREGATED_PREFILL_RANK_TABLE_PATH="/path/to/your/generated/ranktable.json"
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
export VLLM_USE_V1=1
vllm serve /model/Qwen3-30B-A3B \
--host 0.0.0.0 \

8
docs/source/tutorials/multi_node_pd_disaggregation_mooncake.md
View File

@@ -107,7 +107,6 @@ export HCCL_IF_IP=192.0.0.1
export GLOO_SOCKET_IFNAME="eth0" # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
@@ -162,7 +161,6 @@ export HCCL_IF_IP=192.0.0.2
export GLOO_SOCKET_IFNAME="eth0" # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
@@ -217,7 +215,6 @@ export HCCL_IF_IP=192.0.0.3
export GLOO_SOCKET_IFNAME="eth0" # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=2048
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
@@ -274,7 +271,6 @@ export HCCL_IF_IP=192.0.0.4
export GLOO_SOCKET_IFNAME="eth0" # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=2048
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
@@ -338,7 +334,6 @@ export HCCL_IF_IP=192.0.0.1
export GLOO_SOCKET_IFNAME="eth0" # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
@@ -393,7 +388,6 @@ export HCCL_IF_IP=192.0.0.2
export GLOO_SOCKET_IFNAME="eth0" # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
@@ -448,7 +442,6 @@ export HCCL_IF_IP=192.0.0.3
export GLOO_SOCKET_IFNAME="eth0" # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=2048
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
@@ -505,7 +498,6 @@ export HCCL_IF_IP=192.0.0.4
export GLOO_SOCKET_IFNAME="eth0" # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=2048
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10

2
docs/source/tutorials/multi_node_qwen3vl.md
View File

@@ -70,7 +70,6 @@ export TP_SOCKET_IFNAME=$nic_name
export HCCL_SOCKET_IFNAME=$nic_name
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
vllm serve Qwen/Qwen3-VL-235B-A22B-Instruct \
@@ -112,7 +111,6 @@ export TP_SOCKET_IFNAME=$nic_name
export HCCL_SOCKET_IFNAME=$nic_name
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
vllm serve Qwen/Qwen3-VL-235B-A22B-Instruct \

3
docs/source/user_guide/feature_guide/kv_pool_mooncake.md
View File

@@ -82,7 +82,6 @@ The content of the multi_producer.sh script:
export LD_LIBRARY_PATH=/usr/local/Ascend/ascend-toolkit/latest/python/site-packages:$LD_LIBRARY_PATH
export PYTHONPATH=$PYTHONPATH:/xxxxx/vllm
export MOONCAKE_CONFIG_PATH="/xxxxxx/mooncake.json"
export VLLM_USE_V1=1
export ASCEND_RT_VISIBLE_DEVICES=0,1,2,3
export ACL_OP_INIT_MODE=1
export ASCEND_BUFFER_POOL=4:8
@@ -145,7 +144,6 @@ The content of multi_consumer.sh:
export LD_LIBRARY_PATH=/usr/local/Ascend/ascend-toolkit/latest/python/site-packages:$LD_LIBRARY_PATH
export PYTHONPATH=$PYTHONPATH:/xxxxx/vllm
export MOONCAKE_CONFIG_PATH="/xxxxx/mooncake.json"
export VLLM_USE_V1=1
export ASCEND_RT_VISIBLE_DEVICES=4,5,6,7
export ACL_OP_INIT_MODE=1
export ASCEND_BUFFER_POOL=4:8
@@ -246,7 +244,6 @@ Content of mixed_department.sh:
export LD_LIBRARY_PATH=/usr/local/Ascend/ascend-toolkit/latest/python/site-packages:$LD_LIBRARY_PATH
export PYTHONPATH=$PYTHONPATH:/xxxxx/vllm
export MOONCAKE_CONFIG_PATH="/xxxxxx/mooncake.json"
export VLLM_USE_V1=1
export ASCEND_RT_VISIBLE_DEVICES=0,1,2,3
export ACL_OP_INIT_MODE=1
export ASCEND_BUFFER_POOL=4:8

4
examples/disaggregated_prefill_v1/README.md
View File

@@ -41,7 +41,6 @@ export HCCL_SOCKET_IFNAME="eth0"
export DISAGGREGATED_PREFILL_RANK_TABLE_PATH=/vllm-workspace/vllm-ascend/examples/disaggregated_prefill_v1/ranktable.json
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export VLLM_ASCEND_LLMDD_RPC_PORT=5559
vllm serve /models/deepseek_r1_w8a8 \
@@ -82,7 +81,6 @@ export HCCL_SOCKET_IFNAME="eth0"
export DISAGGREGATED_PREFILL_RANK_TABLE_PATH=/vllm-workspace/vllm-ascend/examples/disaggregated_prefill_v1/ranktable.json
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export VLLM_ASCEND_LLMDD_RPC_PORT=5659
vllm serve /models/deepseek_r1_w8a8 \
@@ -126,7 +124,6 @@ export HCCL_SOCKET_IFNAME="eth0"
export DISAGGREGATED_PREFILL_RANK_TABLE_PATH=/vllm-workspace/vllm-ascend/examples/disaggregated_prefill_v1/ranktable.json
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export VLLM_ASCEND_LLMDD_RPC_PORT=5759
vllm serve /models/deepseek_r1_w8a8 \
@@ -168,7 +165,6 @@ export HCCL_SOCKET_IFNAME="eth0"
export DISAGGREGATED_PREFILL_RANK_TABLE_PATH=/vllm-workspace/vllm-ascend/examples/disaggregated_prefill_v1/ranktable.json
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export VLLM_ASCEND_LLMDD_RPC_PORT=5859
vllm serve /models/deepseek_r1_w8a8 \

2
examples/disaggregated_prefill_v1/run_server.sh
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@@ -7,8 +7,6 @@ export DISAGGREGATED_PREFILL_RANK_TABLE_PATH=path-to-rank-table
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
vllm serve model_path \
--host 0.0.0.0 \
--port 20002 \

2
examples/external_online_dp/run_dp_template.sh
View File

@@ -11,8 +11,6 @@ export HCCL_DETERMINISTIC=True
export HCCL_BUFFSIZE=1024
export TASK_QUEUE_ENABLE=1
export VLLM_USE_V1=1
export ASCEND_RT_VISIBLE_DEVICES=$1
vllm serve model_path \

1
examples/run_dp_server.sh
View File

@@ -7,7 +7,6 @@ export HCCL_SOCKET_IFNAME="eth0"
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=100
export VLLM_USE_V1=1
export VLLM_USE_MODELSCOPE=true
export ASCEND_LAUNCH_BLOCKING=0

1
tests/e2e/nightly/features/test_prefix_cache_deepseek_r1_0528_w8a8.py
View File

@@ -72,7 +72,6 @@ async def test_models(model: str) -> None:
"OMP_PROC_BIND": "false",
"HCCL_BUFFSIZE": "1024",
"PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
"VLLM_USE_V1": "1"
}
additional_config = {
"ascend_scheduler_config": {

1
tests/e2e/nightly/models/test_qwq_32b.py
View File

@@ -73,7 +73,6 @@ async def test_models(model: str, mode: str, tp_size: int) -> None:
env_dict = {
"TASK_QUEUE_ENABLE": "1",
"OMP_PROC_BIND": "false",
"VLLM_USE_V1": "1",
"HCCL_OP_EXPANSION_MODE": "AIV",
"VLLM_ASCEND_ENABLE_FLASHCOMM": "1",
"VLLM_ASCEND_ENABLE_TOPK_OPTIMIZE": "1",

1
tests/e2e/pd_disaggreate/run_edge_case_test.sh
View File

@@ -2,7 +2,6 @@
export LCCL_DETERMINISTIC=1
export HCCL_DETERMINISTIC=true
export CLOSE_MATMUL_K_SHIFT=1
export VLLM_USE_V1=1
set -xe

2
tests/e2e/singlecard/test_aclgraph_mem.py
View File

@@ -30,8 +30,6 @@ from vllm_ascend.worker.model_runner_v1 import NPUModelRunner
MODELS = ["Qwen/Qwen3-0.6B", "vllm-ascend/DeepSeek-V2-Lite-W8A8"]
@pytest.mark.skipif(os.getenv("VLLM_USE_V1") == "0",
reason="aclgraph only support on v1")
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("max_tokens", [4])
@patch.dict(os.environ, {"VLLM_ASCEND_FLASHCOMM2_PARALLEL_SIZE": "0"})

1
tests/ut/kv_connector/utils.py
View File

@@ -27,7 +27,6 @@ else:
from vllm.utils.hashing import sha256
EOS_TOKEN_ID = 50256
os.environ["VLLM_USE_V1"] = "1"
def assert_scheduler_empty(scheduler: Scheduler):

2
vllm_ascend/models/qwen3_next.py
View File

@@ -9,7 +9,6 @@ import torch
from einops import rearrange
from torch import nn
from transformers.activations import ACT2FN
from vllm import envs
from vllm.attention import AttentionBackend, AttentionMetadata
from vllm.compilation.decorators import support_torch_compile
from vllm.config import (CacheConfig, ModelConfig, SpeculativeConfig,
@@ -668,7 +667,6 @@ class CustomQwen3NextForCausalLM(Qwen3NextForCausalLM):
scheduler_config = vllm_config.scheduler_config
assert not cache_config.enable_prefix_caching, \
"Qwen3Next currently does not support prefix caching"
assert envs.VLLM_USE_V1, "Qwen3Next requires VLLM_USE_V1"
self.quant_config = vllm_config.quant_config
self.config = config
self.scheduler_config = scheduler_config

6
vllm_ascend/patch/platform/patch_config.py
View File

@@ -1,6 +1,5 @@
import ast
import vllm.envs as envs
from vllm.config.speculative import SpeculativeConfig
from vllm.logger import logger
@@ -163,11 +162,6 @@ def __post_init__(self):
# Replace hf_config for EAGLE draft_model
if self.method in ("eagle", "eagle3"):
if self.enable_chunked_prefill and not envs.VLLM_USE_V1:
raise ValueError(
"Chunked prefill and EAGLE are not compatible "
"when using V0.")
from vllm.transformers_utils.configs import SpeculatorsConfig
from vllm.transformers_utils.configs.eagle import EAGLEConfig

3
vllm_ascend/platform.py
View File

@@ -20,7 +20,6 @@ import os
from typing import TYPE_CHECKING, Optional, Tuple
import torch
import vllm.envs as envs_vllm
from vllm.logger import logger
from vllm.platforms import Platform, PlatformEnum
@@ -117,8 +116,6 @@ class NPUPlatform(Platform):
@classmethod
def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
if not envs_vllm.VLLM_USE_V1:
raise ValueError("vLLM Ascend does not support V0 engine.")
# initialize ascend config from vllm additional_config
ascend_config = init_ascend_config(vllm_config)

10
vllm_ascend/torchair/models/qwen2.py
View File

@@ -21,7 +21,6 @@ from typing import Any, List, Optional, Union
import torch
import torch.nn.functional as F
import vllm
import vllm.envs as envs
from torch import nn
from transformers import Qwen2Config
from vllm.attention import AttentionMetadata, AttentionType
@@ -112,12 +111,9 @@ class CustomQwen2Attention(Qwen2Attention):
is_prefill=False,
is_qwen_torchair=True)
forward_kwargs = {}
if envs.VLLM_USE_V1:
output_shape = q.shape
output = torch.empty(output_shape,
dtype=q.dtype,
device=q.device)
forward_kwargs['output'] = output
output_shape = q.shape
output = torch.empty(output_shape, dtype=q.dtype, device=q.device)
forward_kwargs['output'] = output
attn_output = self.attn.impl.forward(self.attn,
q,

10
vllm_ascend/torchair/models/qwen3_moe.py
View File

@@ -19,7 +19,6 @@
from typing import Any, List, Optional, Union
import torch
import vllm.envs as envs
from torch import nn
from transformers import PretrainedConfig
from vllm.attention import Attention, AttentionMetadata
@@ -244,12 +243,9 @@ class CustomQwen3MoeAttention(Qwen3MoeAttention):
is_prefill=False,
is_qwen_torchair=True)
forward_kwargs = {}
if envs.VLLM_USE_V1:
output_shape = q.shape
output = torch.empty(output_shape,
dtype=q.dtype,
device=q.device)
forward_kwargs['output'] = output
output_shape = q.shape
output = torch.empty(output_shape, dtype=q.dtype, device=q.device)
forward_kwargs['output'] = output
attn_output = self.attn.impl.forward(self.attn,
q,