upgrade vLLM to 0.12.0 tag (#4647)

Upgrade vLLM to v0.12.0 tag

- vLLM version: 86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
- vLLM main:
86e178f7c4

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2025-12-03 23:43:05 +08:00
committed by GitHub
parent 26e8e58cea
commit 3f4c0ea0a0
22 changed files with 97 additions and 47 deletions

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@@ -32,7 +32,7 @@ on:
description: how many pods will be pulled up via lws.yaml, indicates number of nodes we need
vllm_version:
required: false
default: "86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24"
default: "v0.12.0"
type: string
description: vllm version to use
vllm_ascend_remote_url:

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@@ -36,7 +36,7 @@ jobs:
- name: Get vLLM version
run: |
VLLM_COMMIT=86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
VLLM_COMMIT=v0.12.0
echo "VLLM_COMMIT=https://github.com/vllm-project/vllm/commit/$VLLM_COMMIT" >> $GITHUB_ENV
- name: Checkout repository

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@@ -51,7 +51,7 @@ jobs:
strategy:
matrix:
include:
- vllm_branch: 86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
- vllm_branch: v0.12.0
vllm_ascend_branch: main
max-parallel: 1
container:

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@@ -86,7 +86,7 @@ jobs:
tests: tests/e2e/nightly/ops
uses: ./.github/workflows/_e2e_nightly_single_node.yaml
with:
vllm: 86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
vllm: v0.12.0
runner: ${{ matrix.test_config.os }}
tests: ${{ matrix.test_config.tests }}
image: 'swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/vllm-ascend:nightly-a2'
@@ -134,7 +134,7 @@ jobs:
- Qwen3-Next-80B-A3B-Instruct
uses: ./.github/workflows/_e2e_nightly_single_node_models.yaml
with:
vllm: 86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
vllm: v0.12.0
runner: ${{ matrix.test_config.os }}
model_list: ${{ toJson(matrix.test_config.model_list) }}
image: 'swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/cann:8.3.rc2-910b-ubuntu22.04-py3.11'

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@@ -139,7 +139,7 @@ jobs:
tests: tests/e2e/nightly/models/test_glm4_5.py
uses: ./.github/workflows/_e2e_nightly_single_node.yaml
with:
vllm: 86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
vllm: v0.12.0
runner: ${{ matrix.test_config.os }}
image: 'swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/vllm-ascend:nightly-a3'
tests: ${{ matrix.test_config.tests }}

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@@ -50,7 +50,7 @@ jobs:
with:
filters: |
e2e_tracker:
- '.github/workflows/vllm_ascend_test.yaml'
- '.github/workflows/vllm_ascend_test_pr_full.yaml'
- '.github/workflows/_e2e_test.yaml'
- 'vllm_ascend/**'
- 'csrc/**'
@@ -69,7 +69,7 @@ jobs:
name: e2e-full
strategy:
matrix:
vllm_version: [86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24]
vllm_version: [v0.12.0]
needs: [changes]
if: ${{ needs.changes.outputs.e2e_tracker == 'true' }}
uses: ./.github/workflows/_e2e_test.yaml

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@@ -42,7 +42,7 @@ jobs:
lint:
uses: ./.github/workflows/pre-commit.yml
with:
vllm: 86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
vllm: v0.12.0
changes:
runs-on: ubuntu-latest
outputs:
@@ -84,7 +84,7 @@ jobs:
SOC_VERSION: ascend910b1
strategy:
matrix:
vllm_version: [86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24]
vllm_version: [v0.12.0]
steps:
- name: Free up disk space
@@ -137,7 +137,8 @@ jobs:
--ignore tests/ut/torchair/models/test_torchair_deepseek_v2.py \
--ignore tests/ut/models/test_qwen2_vl.py \
--ignore tests/ut/models/test_qwen2_5_vl.py \
--ignore tests/ut/models/test_qwen2_5_vl_without_padding.py
--ignore tests/ut/models/test_qwen2_5_vl_without_padding.py \
--ignore tests/ut/model_loder
- name: Upload coverage to Codecov
# only upload coverage when commits merged
@@ -154,7 +155,7 @@ jobs:
name: e2e-light
strategy:
matrix:
vllm_version: [86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24]
vllm_version: [v0.12.0]
# Note (yikun): If CI resource are limited we can split job into two chain jobs
needs: [lint, changes]
# only trigger e2e test after lint passed and the change is e2e related with pull request.

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@@ -72,7 +72,7 @@ jobs:
- DeepSeek-V2-Lite
uses: ./.github/workflows/_e2e_nightly_single_node_models.yaml
with:
vllm: 86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
vllm: v0.12.0
runner: ${{ matrix.runner }}
image: swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/cann:8.3.rc2-910b-ubuntu22.04-py3.11
model_list: ${{ toJson(matrix.model_list) }}

View File

@@ -48,10 +48,8 @@ RUN pip config set global.index-url ${PIP_INDEX_URL}
# Install vLLM
ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
ARG VLLM_TAG=86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
# Revert this change once VLLM_TAG is specified to branch or tag
# RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
RUN git clone $VLLM_REPO /vllm-workspace/vllm && (cd /vllm-workspace/vllm && git checkout $VLLM_TAG)
ARG VLLM_TAG=v0.12.0
RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
# In x86, triton will be installed by vllm. But in Ascend, triton doesn't work correctly. we need to uninstall it.
RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -v -e /vllm-workspace/vllm/[audio] --extra-index https://download.pytorch.org/whl/cpu/ && \
python3 -m pip uninstall -y triton && \

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@@ -39,10 +39,8 @@ RUN pip config set global.index-url ${PIP_INDEX_URL}
# Install vLLM
ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
ARG VLLM_TAG=86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
# Revert this change once VLLM_TAG is specified to branch or tag
# RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
RUN git clone $VLLM_REPO /vllm-workspace/vllm && (cd /vllm-workspace/vllm && git checkout $VLLM_TAG)
ARG VLLM_TAG=v0.12.0
RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
# In x86, triton will be installed by vllm. But in Ascend, triton doesn't work correctly. we need to uninstall it.
RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -v -e /vllm-workspace/vllm/[audio] --extra-index https://download.pytorch.org/whl/cpu/ && \
python3 -m pip uninstall -y triton && \

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@@ -36,10 +36,8 @@ COPY . /vllm-workspace/vllm-ascend/
# Install vLLM
ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
ARG VLLM_TAG=86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
# Revert this change once VLLM_TAG is specified to branch or tag
# RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
RUN git clone $VLLM_REPO /vllm-workspace/vllm && (cd /vllm-workspace/vllm && git checkout $VLLM_TAG)
ARG VLLM_TAG=v0.12.0
RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
# In x86, triton will be installed by vllm. But in Ascend, triton doesn't work correctly. we need to uninstall it.
RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -e /vllm-workspace/vllm/[audio] --extra-index https://download.pytorch.org/whl/cpu/ && \
python3 -m pip uninstall -y triton && \

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@@ -47,10 +47,8 @@ RUN apt-get update -y && \
# Install vLLM
ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
ARG VLLM_TAG=86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
# Revert this change once VLLM_TAG is specified to branch or tag
# RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
RUN git clone $VLLM_REPO /vllm-workspace/vllm && (cd /vllm-workspace/vllm && git checkout $VLLM_TAG)
ARG VLLM_TAG=v0.12.0
RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
# In x86, triton will be installed by vllm. But in Ascend, triton doesn't work correctly. we need to uninstall it.
RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -v -e /vllm-workspace/vllm/[audio] --extra-index https://download.pytorch.org/whl/cpu/ && \
python3 -m pip uninstall -y triton && \

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@@ -50,10 +50,8 @@ RUN yum update -y && \
# Install vLLM
ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
ARG VLLM_TAG=86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
# Revert this change once VLLM_TAG is specified to branch or tag
# RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
RUN git clone $VLLM_REPO /vllm-workspace/vllm && (cd /vllm-workspace/vllm && git checkout $VLLM_TAG)
ARG VLLM_TAG=v0.12.0
RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
# In x86, triton will be installed by vllm. But in Ascend, triton doesn't work correctly. we need to uninstall it.
RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -e /vllm-workspace/vllm/[audio] --extra-index https://download.pytorch.org/whl/cpu/ && \
python3 -m pip uninstall -y triton && \

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@@ -50,10 +50,8 @@ RUN yum update -y && \
# Install vLLM
ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
ARG VLLM_TAG=86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24
# Revert this change once VLLM_TAG is specified to branch or tag
# RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
RUN git clone $VLLM_REPO /vllm-workspace/vllm && (cd /vllm-workspace/vllm && git checkout $VLLM_TAG)
ARG VLLM_TAG=v0.12.0
RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
# In x86, triton will be installed by vllm. But in Ascend, triton doesn't work correctly. we need to uninstall it.
RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -e /vllm-workspace/vllm/[audio] --extra-index https://download.pytorch.org/whl/cpu/ && \
python3 -m pip uninstall -y triton && \

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@@ -44,7 +44,7 @@ The table below is the release compatibility matrix for vLLM Ascend release.
For main branch of vLLM Ascend, we usually make it compatible with the latest vLLM release and a newer commit hash of vLLM. Please note that this table is usually updated. Please check it regularly.
| vLLM Ascend | vLLM | Python | Stable CANN | PyTorch/torch_npu |
|-------------|--------------|------------------|-------------|--------------------|
| main | v0.11.2 | >= 3.10, < 3.12 | 8.3.RC1 | 2.7.1 / 2.7.1 |
| main | v0.12.0 tag | >= 3.10, < 3.12 | 8.3.RC2 | 2.8.0 / 2.8.0 |
## Release cadence

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@@ -77,7 +77,7 @@ myst_substitutions = {
# CANN image tag
'cann_image_tag': "8.3.rc2-910b-ubuntu22.04-py3.11",
# vllm version in ci
'ci_vllm_version': '86e178f7c4d8c3b0eaf3c8e3f810a83f63b90e24',
'ci_vllm_version': 'v0.12.0',
}
# For cross-file header anchors

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@@ -24,7 +24,7 @@ class TestNPUPlatform(TestBase):
mock_vllm_config.cache_config = MagicMock()
mock_vllm_config.scheduler_config = MagicMock()
mock_vllm_config.speculative_config = None
mock_vllm_config.compilation_config.pass_config.enable_sequence_parallelism = False
mock_vllm_config.compilation_config.pass_config.enable_sp = False
mock_vllm_config.compilation_config.cudagraph_mode = None
return mock_vllm_config

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@@ -23,6 +23,7 @@ if HAS_TRITON:
# isort: off
import vllm_ascend.patch.platform.patch_sched_yield # noqa
import vllm_ascend.patch.worker.patch_distributed # noqa
import vllm_ascend.patch.worker.patch_deepseek # noqa
import vllm_ascend.patch.worker.patch_roberta # noqa
import vllm_ascend.patch.worker.patch_weight_loader # noqa
import vllm_ascend.patch.worker.patch_multimodal_merge # noqa

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@@ -0,0 +1,60 @@
from itertools import islice
import torch
from vllm.distributed import get_pp_group
from vllm.model_executor.models.deepseek_v2 import (DeepseekV2Model,
_get_llama_4_scaling)
from vllm.sequence import IntermediateTensors
def forward(
self,
input_ids,
positions,
intermediate_tensors,
inputs_embeds,
):
if get_pp_group().is_first_rank:
if inputs_embeds is not None:
hidden_states = inputs_embeds
else:
hidden_states = self.embed_input_ids(input_ids)
residual = None
else:
assert intermediate_tensors is not None
hidden_states = intermediate_tensors["hidden_states"]
residual = intermediate_tensors["residual"]
# Compute llama 4 scaling once per forward pass if enabled
# Note(wxy): This is a hack fix to avoid graph mode error for torch 2.8
# We'll find a better way to remove this patch.
try:
llama_4_scaling_config = getattr(self.config, "llama_4_scaling")
except AttributeError:
llama_4_scaling_config = None
llama_4_scaling: torch.Tensor | None
if llama_4_scaling_config is not None:
llama_4_scaling = _get_llama_4_scaling(
original_max_position_embeddings=llama_4_scaling_config[
"original_max_position_embeddings"],
scaling_beta=llama_4_scaling_config["beta"],
positions=positions,
)
else:
llama_4_scaling = None
for layer in islice(self.layers, self.start_layer, self.end_layer):
hidden_states, residual = layer(positions, hidden_states, residual,
llama_4_scaling)
if not get_pp_group().is_last_rank:
return IntermediateTensors({
"hidden_states": hidden_states,
"residual": residual
})
hidden_states, _ = self.norm(hidden_states, residual)
return hidden_states
DeepseekV2Model.forward = forward

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@@ -159,7 +159,8 @@ class NPUPlatform(Platform):
compilation_config.splitting_ops = []
compilation_config.cudagraph_num_of_warmups = 1
compilation_config.pass_config.enable_fusion = False
compilation_config.pass_config.fuse_norm_quant = False
compilation_config.pass_config.fuse_act_quant = False
if compilation_config.mode not in [
CompilationMode.NONE, CompilationMode.VLLM_COMPILE
@@ -194,7 +195,7 @@ class NPUPlatform(Platform):
# to ascend ops && hardwares. We update these sizes here to improve
# default performance.
update_default_aclgraph_sizes(vllm_config)
# TODO delete graph size update here when compilation_config.pass_config.enable_sequence_parallelism
# TODO delete graph size update here when compilation_config.pass_config.enable_sp
# is supported by vllm-ascend.
if vllm_config.parallel_config.tensor_parallel_size > 1 and not vllm_config.model_config.enforce_eager and \
enable_sp(vllm_config):

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@@ -315,8 +315,8 @@ class CustomQwen3MoeDecoderLayer(Qwen3MoeDecoderLayer):
eps=config.rms_norm_eps)
self.enable_sequence_parallelism = (
vllm_config.compilation_config.pass_config.
enable_sequence_parallelism if vllm_config is not None else False)
vllm_config.compilation_config.pass_config.enable_sp
if vllm_config is not None else False)
def forward(
self,
@@ -488,7 +488,7 @@ class CustomQwen3MoeForCausalLM(Qwen3MoeForCausalLM):
self.make_empty_intermediate_tensors = (
self.model.make_empty_intermediate_tensors)
self.enable_sequence_parallelism = vllm_config.compilation_config.pass_config.enable_sequence_parallelism
self.enable_sequence_parallelism = vllm_config.compilation_config.pass_config.enable_sp
# Set MoE hyperparameters
self.expert_weights: list[torch.Tensor] = []

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@@ -773,8 +773,7 @@ def enable_sp(vllm_config=None, enable_shared_expert_dp: bool = False) -> bool:
from vllm.config import get_current_vllm_config
vllm_config = get_current_vllm_config()
_ENABLE_SP = (
vllm_config.compilation_config.pass_config.
enable_sequence_parallelism
vllm_config.compilation_config.pass_config.enable_sp
or envs_ascend.VLLM_ASCEND_ENABLE_FLASHCOMM1
# Flash comm 1 should be enabled by env VLLM_ASCEND_ENABLE_FLASHCOMM1
# We retain the env VLLM_ASCEND_ENABLE_FLASHCOMM here for backward compatibility.