[v0.9.1][DP][V1] Fix rank set in DP scenario & Bump torch-npu version to 2.5.1.post1.dev20250528 (#1247)

### What this PR does / why we need it?
Cherry-pick form #1235

1. Fix rank set in DP scenario. The new poc version of torch-npu support
setting `ASCEND_RT_VISIBLE_DEVICES` dynamically, thus we could use the
rank set in `DPEngineCoreProc` directly instead of calculating local
rank across dp by hand in the patched `_init_data_parallel`

Closes: #1170

2. Bump torch-npu version to 2.5.1.post1.dev20250528

Closes: #1242
Closes: #1232

### How was this patch tested?
CI passed with new added test.

---------

Signed-off-by: Icey <1790571317@qq.com>
Signed-off-by: MengqingCao <cmq0113@163.com>
Co-authored-by: Icey <1790571317@qq.com>

Author: MengqingCao

.github/workflows/accuracy_test.yaml

@@ -173,6 +173,8 @@ jobs:
 
       - name: Install vllm-project/vllm-ascend
         working-directory: ./vllm-ascend
+        env:
+          PIP_EXTRA_INDEX_URL: https://mirrors.huaweicloud.com/ascend/repos/pypi
         run: |
           pip install -r requirements-dev.txt
           pip install -e .

.github/workflows/image_openeuler.yml

@@ -19,6 +19,12 @@ on:
       - '.github/workflows/image_openeuler.yml'
       - 'Dockerfile.openEuler'
       - 'vllm_ascend/**'
+      - 'setup.py'
+      - 'pyproject.toml'
+      - 'requirements.txt'
+      - 'cmake/**'
+      - 'CMakeLists.txt'
+      - 'csrc/**'
   push:
     # Publish image when tagging, the Dockerfile in tag will be build as tag image
     branches:

.github/workflows/image_ubuntu.yml

@@ -19,6 +19,12 @@ on:
       - '.github/workflows/image_ubuntu.yml'
       - 'Dockerfile'
       - 'vllm_ascend/**'
+      - 'setup.py'
+      - 'pyproject.toml'
+      - 'requirements.txt'
+      - 'cmake/**'
+      - 'CMakeLists.txt'
+      - 'csrc/**'
   push:
     # Publish image when tagging, the Dockerfile in tag will be build as tag image
     branches:

.github/workflows/nightly_benchmarks.yaml

@@ -111,6 +111,8 @@ jobs:
           VLLM_TARGET_DEVICE=empty pip install -e .
 
       - name: Install vllm-project/vllm-ascend
+        env:
+          PIP_EXTRA_INDEX_URL: https://mirrors.huaweicloud.com/ascend/repos/pypi
         run: |
           pip install -e .
           pip install -r benchmarks/requirements-bench.txt

.github/workflows/vllm_ascend_test.yaml

@@ -167,6 +167,8 @@ jobs:
           VLLM_TARGET_DEVICE=empty pip install -e .
 
       - name: Install vllm-project/vllm-ascend
+        env:
+          PIP_EXTRA_INDEX_URL: https://mirrors.huaweicloud.com/ascend/repos/pypi
         run: |
           pip install -r requirements-dev.txt
           pip install -v -e .

.github/workflows/vllm_ascend_test_long_term.yaml

@@ -85,6 +85,8 @@ jobs:
           VLLM_TARGET_DEVICE=empty pip install -e .
 
       - name: Install vllm-project/vllm-ascend
+        env:
+          PIP_EXTRA_INDEX_URL: https://mirrors.huaweicloud.com/ascend/repos/pypi
         run: |
           pip install -r requirements-dev.txt
           pip install -v -e .

.github/workflows/vllm_ascend_test_pd.yaml

@@ -94,6 +94,8 @@ jobs:
           VLLM_TARGET_DEVICE=empty pip install -e .
 
       - name: Install vllm-project/vllm-ascend
+        env:
+          PIP_EXTRA_INDEX_URL: https://mirrors.huaweicloud.com/ascend/repos/pypi
         run: |
           pip install -r requirements-dev.txt
           pip install -v -e .

Dockerfile

@@ -46,7 +46,8 @@ RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -v -e /vllm-workspace/vllm
 
 # Install vllm-ascend
 # Append `libascend_hal.so` path (devlib) to LD_LIBRARY_PATH
-RUN source /usr/local/Ascend/ascend-toolkit/set_env.sh && \
+RUN export PIP_EXTRA_INDEX_URL=https://mirrors.huaweicloud.com/ascend/repos/pypi && \
+    source /usr/local/Ascend/ascend-toolkit/set_env.sh && \
     source /usr/local/Ascend/nnal/atb/set_env.sh && \
     export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/Ascend/ascend-toolkit/latest/`uname -i`-linux/devlib && \
     python3 -m pip install -v -e /vllm-workspace/vllm-ascend/ --extra-index https://download.pytorch.org/whl/cpu/ && \

Dockerfile.openEuler

@@ -43,7 +43,8 @@ RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -e /vllm-workspace/vllm/ -
     python3 -m pip cache purge
 
 # Install vllm-ascend
-RUN source /usr/local/Ascend/ascend-toolkit/set_env.sh && \
+RUN export PIP_EXTRA_INDEX_URL=https://mirrors.huaweicloud.com/ascend/repos/pypi && \
+    source /usr/local/Ascend/ascend-toolkit/set_env.sh && \
     source /usr/local/Ascend/nnal/atb/set_env.sh && \
     export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/Ascend/ascend-toolkit/latest/`uname -i`-linux/devlib && \
     python3 -m pip install -v -e /vllm-workspace/vllm-ascend/ --extra-index https://download.pytorch.org/whl/cpu/ && \

README.md

@@ -38,7 +38,7 @@ By using vLLM Ascend plugin, popular open-source models, including Transformer-l
 - Software:
   * Python >= 3.9, < 3.12
   * CANN >= 8.1.RC1
-  * PyTorch >= 2.5.1, torch-npu >= 2.5.1
+  * PyTorch >= 2.5.1, torch-npu >= 2.5.1.post1.dev20250528
   * vLLM (the same version as vllm-ascend)
 
 ## Getting Started

README.zh.md

@@ -39,7 +39,7 @@ vLLM 昇腾插件 (`vllm-ascend`) 是一个由社区维护的让vLLM在Ascend NP
 - 软件：
   * Python >= 3.9, < 3.12
   * CANN >= 8.1.RC1
-  * PyTorch >= 2.5.1, torch-npu >= 2.5.1
+  * PyTorch >= 2.5.1, torch-npu >= 2.5.1.post1.dev20250528
   * vLLM (与vllm-ascend版本一致)
 
 ## 开始使用

docs/source/installation.md

@@ -9,11 +9,11 @@ This document describes how to install vllm-ascend manually.
 - A hardware with Ascend NPU. It's usually the Atlas 800 A2 series.
 - Software:
 
-    | Software  | Supported version | Note                                   |
-    |-----------|-------------------|----------------------------------------| 
-    | CANN      | >= 8.1.RC1        | Required for vllm-ascend and torch-npu |
-    | torch-npu | >= 2.5.1          | Required for vllm-ascend               |
-    | torch     | >= 2.5.1          | Required for torch-npu and vllm        |
+    | Software      | Supported version                | Note                                      |
+    |---------------|----------------------------------|-------------------------------------------|
+    | CANN          | >= 8.1.RC1                       | Required for vllm-ascend and torch-npu    |
+    | torch-npu     | >= 2.5.1.post1.dev20250528       | Required for vllm-ascend                  |
+    | torch         | >= 2.5.1                         | Required for torch-npu and vllm           |
 
 You have 2 way to install:
 - **Using pip**: first prepare env manually or via CANN image, then install `vllm-ascend` using pip.
@@ -156,6 +156,7 @@ cd ..
 # Install vLLM Ascend
 git clone  --depth 1 --branch |vllm_ascend_version| https://github.com/vllm-project/vllm-ascend.git
 cd vllm-ascend
+export PIP_EXTRA_INDEX_URL=https://mirrors.huaweicloud.com/ascend/repos/pypi
 pip install -v -e .
 cd ..
 ```

requirements.txt

@@ -10,7 +10,6 @@ pyyaml
 scipy
 setuptools>=64
 setuptools-scm>=8
-torch-npu==2.5.1
 torch>=2.5.1
 torchvision<0.21.0
 wheel
@@ -21,3 +20,8 @@ quart
 
 # Required for N-gram speculative decoding
 numba
+
+# Install torch_npu
+--pre
+--extra-index-url https://mirrors.huaweicloud.com/ascend/repos/pypi
+torch-npu==2.5.1.post1.dev20250528

setup.py

@@ -152,7 +152,7 @@ def configure(self, ext: CMakeExtension) -> None:
             # if pybind11 is installed via pip
             pybind11_cmake_path = (subprocess.check_output(
                 [python_executable, "-m", "pybind11",
-                 "--cmake"]).decode().strip())
+                 "--cmakedir"]).decode().strip())
         except subprocess.CalledProcessError as e:
             # else specify pybind11 path installed from source code on CI container
             raise RuntimeError(f"CMake configuration failed: {e}")

tests/multicard/test_data_parallel.py

@@ -0,0 +1,66 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# Copyright 2023 The vLLM team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+"""
+Compare the outputs of vLLM with and without aclgraph.
+Run `pytest tests/multicard/test_data_parallel.py`.
+"""
+
+import os
+
+import pytest
+
+from tests.conftest import VllmRunner
+from tests.model_utils import check_outputs_equal
+
+MODELS = ["Qwen/Qwen2.5-0.5B-Instruct"]
+
+
+@pytest.mark.skipif(True, reason="OPEN ME when dp is supported on A2")
+@pytest.mark.skipif(os.getenv("VLLM_USE_V1") == "0",
+                    reason="Data parallel only support on v1")
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("max_tokens", [32])
+def test_data_parallel_correctness(
+    model: str,
+    max_tokens: int,
+) -> None:
+    example_prompts = [
+        "Hello, my name is", "The president of the United States is",
+        "The capital of France is", "The future of AI is"
+    ]
+
+    with VllmRunner(model_name=model,
+                    max_model_len=1024,
+                    max_num_seqs=16,
+                    data_parallel_size=2,
+                    distributed_executor_backend="mp") as vllm_model:
+        vllm_dp_outputs = vllm_model.generate_greedy(example_prompts,
+                                                     max_tokens)
+
+    with VllmRunner(
+            model_name=model,
+            max_model_len=1024,
+            max_num_seqs=16,
+    ) as vllm_model:
+        vllm_outputs = vllm_model.generate_greedy(example_prompts, max_tokens)
+
+    check_outputs_equal(
+        outputs_0_lst=vllm_outputs,
+        outputs_1_lst=vllm_dp_outputs,
+        name_0="vllm_outputs",
+        name_1="vllm_dp_outputs",
+    )

vllm_ascend/patch/platform/patch_common/patch_distributed.py

@@ -21,10 +21,9 @@
 import vllm.distributed
 import vllm.envs as envs
 from torch.distributed import ProcessGroup
-from vllm.config import ParallelConfig, VllmConfig
+from vllm.config import ParallelConfig
 from vllm.distributed.utils import \
     stateless_init_torch_distributed_process_group
-from vllm.v1.engine.core import DPEngineCoreProc
 
 
 def ascend_destroy_model_parallel():
@@ -79,21 +78,6 @@ def stateless_init_dp_group(self) -> "ProcessGroup":
     return dp_group
 
 
-def _init_data_parallel(self, vllm_config: VllmConfig):
-    # Configure NPUs and stateless process group for data parallel.
-    dp_rank = vllm_config.parallel_config.data_parallel_rank
-    dp_size = vllm_config.parallel_config.data_parallel_size
-    local_dp_rank = vllm_config.parallel_config.data_parallel_rank_local
-
-    assert dp_size > 1
-    assert 0 <= local_dp_rank <= dp_rank < dp_size
-
-    self.local_dp_rank = local_dp_rank
-    self.dp_group = vllm_config.parallel_config.stateless_init_dp_group()
-    self.current_wave = 0
-
-
 vllm.distributed.parallel_state.destroy_model_parallel = ascend_destroy_model_parallel
-DPEngineCoreProc._init_data_parallel = _init_data_parallel
 ParallelConfig.get_next_dp_init_port = parallel_config_get_dp_port
 ParallelConfig.stateless_init_dp_group = stateless_init_dp_group

vllm_ascend/worker/worker_v1.py

@@ -75,12 +75,6 @@ def __init__(
                          distributed_init_method=distributed_init_method,
                          is_driver_worker=is_driver_worker)
 
-        # NOTE(Yizhou): Since we do not set ASCEND_RT_VISIBLE_DEVICES in
-        # vllm_ascend, we need to set the device id manually.
-        local_dp_rank = self.vllm_config.parallel_config.data_parallel_rank_local
-        world_size = self.vllm_config.parallel_config.world_size
-        self.local_rank_across_dp = local_dp_rank * world_size + self.local_rank
-
         # Try to import mindie_turbo to accelerate vLLM inference.
         try_register_lib(
             "mindie_turbo",
@@ -124,7 +118,7 @@ def initialize_cache(self, num_gpu_blocks: int,
 
     def init_device(self):
         if self.device_config.device.type == "npu":
-            self.device = torch.device(f"npu:{self.local_rank_across_dp}")
+            self.device = torch.device(f"npu:{self.local_rank}")
             NPUPlatform.set_device(self.device)
             NPUPlatform.empty_cache()
             self.init_npu_memory = NPUPlatform.mem_get_info()[0]