[CI] Upgrade vllm to 0.9.1 (#1165)

wangxiyuan · web-flow · commit 4f5964420e27 · 2025-06-11T16:33:11.000+08:00
1. upgrade vllm to 0.9.1. 0.9.0 is not supported for main branch now.
keep doc to 0.9.0 until we release the first 0.9.1 release.
2. disable V0 test for PR
3. move actionlint check to lint job

Signed-off-by: wangxiyuan &lt;wangxiyuan1007@gmail.com&gt;
diff --git a/.github/workflows/accuracy_test.yaml b/.github/workflows/accuracy_test.yaml
@@ -34,8 +34,7 @@ on:
         # Current supported vLLM versions
         options:
           - main
-          - v0.9.0.1
-          - v0.9.0
+          - v0.9.1
           - v0.7.3
       vllm-ascend-version:
         description: 'vllm-ascend version:'
@@ -159,7 +158,7 @@ jobs:
           repository: vllm-project/vllm
           path: ./vllm-empty
           # Please also update this when bump matched version
-          ref: ${{ github.event.inputs.vllm-version || 'v0.9.0' }}
+          ref: ${{ github.event.inputs.vllm-version || 'v0.9.1' }}
 
       - name: Install vllm-project/vllm from source
         working-directory: ./vllm-empty
diff --git a/.github/workflows/actionlint.yml b/.github/workflows/actionlint.yml
diff --git a/.github/workflows/nightly_benchmarks.yaml b/.github/workflows/nightly_benchmarks.yaml
@@ -50,7 +50,7 @@ jobs:
     strategy:
       matrix:
         include:
-          - vllm_branch: v0.9.0
+          - vllm_branch: v0.9.1
             vllm_ascend_branch: main
     container:
       image: m.daocloud.io/quay.io/ascend/cann:8.1.rc1-910b-ubuntu22.04-py3.10
diff --git a/.github/workflows/vllm_ascend_test.yaml b/.github/workflows/vllm_ascend_test.yaml
@@ -33,6 +33,9 @@ on:
       - '!benchmarks/**'
       - 'tools/mypy.sh'
       - 'mypy.ini'
+      - '.github/workflows/*.ya?ml'
+      - '.github/workflows/actionlint.*'
+      - '.github/workflows/matchers/actionlint.json'
 
 # Bash shells do not use ~/.profile or ~/.bashrc so these shells need to be explicitly
 # declared as "shell: bash -el {0}" on steps that need to be properly activated.
@@ -87,6 +90,13 @@ jobs:
           repository: vllm-project/vllm
           path: vllm-empty
 
+      - name: Actionlint Check
+        env:
+          SHELLCHECK_OPTS: --exclude=SC2046,SC2006,SC2086
+        run: |
+          echo "::add-matcher::.github/workflows/matchers/actionlint.json"
+          tools/actionlint.sh -color
+
       - name: Install vllm-project/vllm from source
         working-directory: vllm-empty
         run: |
@@ -105,7 +115,7 @@ jobs:
       max-parallel: 2
       matrix:
         os: [linux-arm64-npu-1, linux-arm64-npu-4]
-        vllm_version: [main, v0.9.0]
+        vllm_version: [main, v0.9.1]
     concurrency:
       group: >
         ${{
@@ -193,6 +203,7 @@ jobs:
           fi
 
       - name: Run vllm-project/vllm-ascend test on V0 engine
+        if: ${{ github.event_name == 'schedule' }}
         env:
           VLLM_USE_V1: 0
         run: |
diff --git a/.github/workflows/vllm_ascend_test_long_term.yaml b/.github/workflows/vllm_ascend_test_long_term.yaml
@@ -43,7 +43,7 @@ jobs:
       max-parallel: 2
       matrix:
         os: [linux-arm64-npu-1, linux-arm64-npu-4]
-        vllm_version: [main, v0.9.0]
+        vllm_version: [main, v0.9.1]
     name: vLLM Ascend long term test
     runs-on: ${{ matrix.os }}
     container:
diff --git a/.github/workflows/vllm_ascend_test_pd.yaml b/.github/workflows/vllm_ascend_test_pd.yaml
@@ -41,7 +41,7 @@ jobs:
     if: ${{ contains(github.event.pull_request.labels.*.name, 'pd-test') && contains(github.event.pull_request.labels.*.name, 'ready-for-test') || github.event_name == 'schedule' }}
     strategy:
       matrix:
-        vllm_verison: [main, v0.9.0]
+        vllm_verison: [main, v0.9.1]
     name: vLLM Ascend prefilling decoding disaggregation test
     runs-on: linux-arm64-npu-static-8
 
diff --git a/Dockerfile b/Dockerfile
@@ -37,7 +37,7 @@ 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=v0.9.0
+ARG VLLM_TAG=v0.9.1
 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/ --extra-index https://download.pytorch.org/whl/cpu/ && \
diff --git a/Dockerfile.openEuler b/Dockerfile.openEuler
@@ -34,7 +34,7 @@ COPY . /vllm-workspace/vllm-ascend/
 
 # Install vLLM
 ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
-ARG VLLM_TAG=v0.9.0
+ARG VLLM_TAG=v0.9.1
 
 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.
diff --git a/tests/singlecard/compile/test_simple.py b/tests/singlecard/compile/test_simple.py
@@ -14,8 +14,6 @@
                          set_current_vllm_config)
 from vllm.utils import direct_register_custom_op
 
-from vllm_ascend.utils import vllm_version_is
-
 global_counter = 0
 
 # create a library to hold the custom op
@@ -93,28 +91,14 @@ def test_simple_piecewise_compile():
         model = SillyModel(vllm_config=vllm_config, prefix="")
 
     inputs = torch.randn(100).npu()
-
-    if vllm_version_is("0.9.0"):
-        kwargs = {
-            "num_graphs_seen": 1,  # one graph for the model
-            "num_piecewise_graphs_seen": 5,  # 2 * num_layers + 1
-            "num_piecewise_capturable_graphs_seen": 3,  # 1 + num_layers
-            "num_backend_compilations":
-            3,  # num_piecewise_capturable_graphs_seen
-            "num_cudagraph_caputured":
-            6  # num_cudagraph_sizes * num_piecewise_capturable_graphs_seen
-        }
-    else:
-        kwargs = {
-            "num_graphs_seen": 1,  # one graph for the model
-            "num_piecewise_graphs_seen": 5,  # 2 * num_layers + 1
-            "num_piecewise_capturable_graphs_seen": 3,  # 1 + num_layers
-            "num_backend_compilations":
-            3,  # num_piecewise_capturable_graphs_seen
-            "num_cudagraph_captured":
-            6  # num_cudagraph_sizes * num_piecewise_capturable_graphs_seen
-        }
-
+    kwargs = {
+        "num_graphs_seen": 1,  # one graph for the model
+        "num_piecewise_graphs_seen": 5,  # 2 * num_layers + 1
+        "num_piecewise_capturable_graphs_seen": 3,  # 1 + num_layers
+        "num_backend_compilations": 3,  # num_piecewise_capturable_graphs_seen
+        "num_cudagraph_captured":
+        6  # num_cudagraph_sizes * num_piecewise_capturable_graphs_seen
+    }
     with compilation_counter.expect(kwargs):
 
         model(inputs)
diff --git a/tests/singlecard/test_scheduler.py b/tests/singlecard/test_scheduler.py
@@ -31,7 +31,6 @@
 from vllm.v1.structured_output import StructuredOutputManager
 
 from vllm_ascend.core.scheduler import AscendScheduler
-from vllm_ascend.utils import vllm_version_is
 
 EOS_TOKEN_ID = 50256
 
@@ -87,27 +86,15 @@ def create_scheduler(
     vllm_config = VllmConfig(scheduler_config=scheduler_config,
                              model_config=model_config,
                              cache_config=cache_config)
-
-    if vllm_version_is("0.9.0"):
-        kv_cache_config = KVCacheConfig(
-            num_blocks=10000,  # A large number of blocks to hold all requests
-            tensors={},
-            kv_cache_groups=[
-                KVCacheGroupSpec(['layer'],
-                                 FullAttentionSpec(16, 1, 1, torch.float32,
-                                                   False))
-            ],
-        )
-    else:
-        kv_cache_config = KVCacheConfig(
-            num_blocks=10000,  # A large number of blocks to hold all requests
-            kv_cache_tensors=[KVCacheTensor(size=1024, shared_by=[1])],
-            kv_cache_groups=[
-                KVCacheGroupSpec(['layer'],
-                                 FullAttentionSpec(16, 1, 1, torch.float32,
-                                                   False, None))
-            ],
-        )
+    kv_cache_config = KVCacheConfig(
+        num_blocks=10000,  # A large number of blocks to hold all requests
+        kv_cache_tensors=[KVCacheTensor(size=1024, shared_by=[1])],
+        kv_cache_groups=[
+            KVCacheGroupSpec(['layer'],
+                             FullAttentionSpec(16, 1, 1, torch.float32, False,
+                                               None))
+        ],
+    )
     cache_config.num_gpu_blocks = 10000
     return AscendScheduler(
         vllm_config,
@@ -135,27 +122,15 @@ def create_requests(num_requests: int,
         else:
             mm_position = None
             mm_inputs = None
-        if vllm_version_is("0.9.0"):
-            request = Request(
-                request_id=f"{i}",
-                prompt_token_ids=[i] * num_tokens,
-                sampling_params=sampling_params,
-                multi_modal_inputs=mm_inputs,
-                multi_modal_placeholders=mm_position,
-                multi_modal_hashes=None,
-                arrival_time=0,
-                eos_token_id=EOS_TOKEN_ID,
-            )
-        else:
-            request = Request(
-                request_id=f"{i}",
-                prompt_token_ids=[i] * num_tokens,
-                sampling_params=sampling_params,
-                multi_modal_inputs=mm_inputs,
-                multi_modal_placeholders=mm_position,
-                multi_modal_hashes=None,
-                eos_token_id=EOS_TOKEN_ID,
-            )
+        request = Request(
+            request_id=f"{i}",
+            prompt_token_ids=[i] * num_tokens,
+            sampling_params=sampling_params,
+            multi_modal_inputs=mm_inputs,
+            multi_modal_placeholders=mm_position,
+            multi_modal_hashes=None,
+            eos_token_id=EOS_TOKEN_ID,
+        )
         requests.append(request)
     return requests
 
diff --git a/vllm_ascend/compilation/piecewise_backend.py b/vllm_ascend/compilation/piecewise_backend.py
@@ -31,8 +31,6 @@
 from vllm.logger import logger
 from vllm.utils import weak_ref_tensors
 
-from vllm_ascend.utils import vllm_version_is
-
 
 @dataclasses.dataclass
 class ConcreteSizeEntry:
@@ -206,11 +204,7 @@ def __call__(self, *args) -> Any:
             # to save memory
             entry.output = weak_ref_tensors(output)
             entry.aclgraph = aclgraph
-
-            if vllm_version_is("0.9.0"):
-                compilation_counter.num_cudagraph_caputured += 1
-            else:
-                compilation_counter.num_cudagraph_captured += 1
+            compilation_counter.num_cudagraph_captured += 1
 
             # important: we need to return the output, rather than
             # the weak ref of the output, so that pytorch can correctly
diff --git a/vllm_ascend/core/scheduler.py b/vllm_ascend/core/scheduler.py
@@ -29,8 +29,6 @@
 from vllm.v1.request import Request, RequestStatus
 from vllm.v1.structured_output import StructuredOutputManager
 
-from vllm_ascend.utils import vllm_version_is
-
 
 class AscendScheduler(Scheduler):
     """This Scheduler extends vllm's original v1 scheduler
@@ -129,12 +127,7 @@ def skip_cur_request():
                 continue
 
             assert num_new_tokens > 0
-
-            if vllm_version_is("0.9.0"):
-                blocks = computed_blocks.blocks
-            else:
-                blocks = computed_blocks.blocks[0]
-
+            blocks = computed_blocks.blocks[0]
             watermark = getattr(self.scheduler_config, "watermark", 0.01)
             if not self._check_watermark_for_prefill(request, num_new_tokens,
                                                      blocks, watermark):
@@ -330,14 +323,8 @@ def _check_watermark_for_prefill(self,
                                len(computed_blocks) * self.block_size)
         num_required_blocks = cdiv(num_new_tokens + num_computed_tokens,
                                    self.block_size)
-
-        if vllm_version_is("0.9.0"):
-            req_blocks = self.kv_cache_manager.single_type_manager.req_to_blocks[
-                request.request_id]
-        else:
-            req_blocks = self.kv_cache_manager.coordinator.get_blocks(
-                request.request_id)
-
+        req_blocks = self.kv_cache_manager.coordinator.get_blocks(
+            request.request_id)
         num_new_blocks = (num_required_blocks - len(req_blocks) -
                           len(computed_blocks))
         num_evictable_computed_blocks = sum(1 for blk in computed_blocks
diff --git a/vllm_ascend/patch/__init__.py b/vllm_ascend/patch/__init__.py
@@ -24,9 +24,9 @@
 #           each worker's `__init__` function.
 #
 # Then in each kind of patch, there are three folders:
-# - patch_0_9_0: contains the patches applied when vllm version is 0.9.0.
+# - patch_0_9_1: contains the patches applied when vllm version is 0.9.1.
 # - patch_main: contains the patches applied when vllm version is main branch.
-# - patch_common: contains the patches applied in both 0.9.0 and main branch.
+# - patch_common: contains the patches applied in both 0.9.1 and main branch.
 #
 # Once a new patch is added in vllm-ascend, please add the patch description into this file as well.
 # ----------------------------------------------------------------------------------
@@ -35,17 +35,6 @@
 # --------------------------------
 # * Platform Patch:
 # =================
-# ** File: platform/patch_0_9_0/patch_distributed.py**
-# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#   1. `vllm.distributed.utils.stateless_init_torch_distributed_process_group()`
-#    Why:
-#       vllm distributed use gloo backend by default to initialize stateless process group, but we want to use hccl here
-#    How：
-#       Add hccl backend to the `stateless_init_torch_distributed_process_group`
-#    Related PR (if no, explain why):
-#       https://github.com/vllm-project/vllm/pull/18763
-#    Future Plan:
-#       Remove this patch once vllm is upgraded to 0.9.1
 # ** File: platform/patch_common/patch_distributed.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.distributed.parallel_state.destroy_model_parallel()`
diff --git a/vllm_ascend/patch/platform/__init__.py b/vllm_ascend/patch/platform/__init__.py
@@ -17,8 +17,8 @@
 from vllm_ascend.utils import vllm_version_is
 
 # Import specific patches for different versions
-if vllm_version_is("0.9.0"):
-    from vllm_ascend.patch.platform import patch_0_9_0  # noqa: F401
+if vllm_version_is("0.9.1"):
+    from vllm_ascend.patch.platform import patch_0_9_1  # noqa: F401
     from vllm_ascend.patch.platform import patch_common  # noqa: F401
 else:
     from vllm_ascend.patch.platform import patch_common  # noqa: F401
diff --git a/vllm_ascend/patch/platform/patch_0_9_0/patch_distributed.py b/vllm_ascend/patch/platform/patch_0_9_0/patch_distributed.py
diff --git a/vllm_ascend/patch/platform/patch_0_9_1/__init__.py b/vllm_ascend/patch/platform/patch_0_9_1/__init__.py
diff --git a/vllm_ascend/patch/worker/__init__.py b/vllm_ascend/patch/worker/__init__.py
diff --git a/vllm_ascend/patch/worker/patch_0_9_1/__init__.py b/vllm_ascend/patch/worker/patch_0_9_1/__init__.py
diff --git a/vllm_ascend/worker/model_runner_v1.py b/vllm_ascend/worker/model_runner_v1.py
