This PR upgrade CANN from 8.2rc1 to 8.3rc1 and remove the CANN version
check logic.
TODO: we notice that UT runs failed with CANN 8.3 image. So the base
image for UT is still 8.2. We'll fix it later.
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
201 lines
8.0 KiB
YAML
201 lines
8.0 KiB
YAML
name: 'e2e test'
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on:
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workflow_call:
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inputs:
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vllm:
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required: true
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type: string
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runner:
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required: true
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type: string
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image:
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required: true
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type: string
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type:
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required: true
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type: string
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jobs:
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e2e:
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name: singlecard
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runs-on: ${{ inputs.runner }}-1
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container:
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image: ${{ inputs.image }}
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env:
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VLLM_LOGGING_LEVEL: ERROR
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VLLM_USE_MODELSCOPE: True
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steps:
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- name: Check npu and CANN info
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run: |
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npu-smi info
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cat /usr/local/Ascend/ascend-toolkit/latest/"$(uname -i)"-linux/ascend_toolkit_install.info
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- name: Config mirrors
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run: |
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sed -Ei 's@(ports|archive).ubuntu.com@cache-service.nginx-pypi-cache.svc.cluster.local:8081@g' /etc/apt/sources.list
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pip config set global.index-url http://cache-service.nginx-pypi-cache.svc.cluster.local/pypi/simple
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pip config set global.trusted-host cache-service.nginx-pypi-cache.svc.cluster.local
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apt-get update -y
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apt install git -y
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- name: Checkout vllm-project/vllm-ascend repo
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uses: actions/checkout@v4
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- name: Install system dependencies
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run: |
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apt-get -y install `cat packages.txt`
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apt-get -y install gcc g++ cmake libnuma-dev
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- name: Checkout vllm-project/vllm repo
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uses: actions/checkout@v4
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with:
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repository: vllm-project/vllm
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ref: ${{ inputs.vllm }}
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path: ./vllm-empty
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fetch-depth: 1
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- name: Install vllm-project/vllm from source
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working-directory: ./vllm-empty
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run: |
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VLLM_TARGET_DEVICE=empty pip install -e .
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- name: Install vllm-project/vllm-ascend
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env:
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PIP_EXTRA_INDEX_URL: https://mirrors.huaweicloud.com/ascend/repos/pypi
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run: |
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pip install -r requirements-dev.txt
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pip install -v -e .
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- name: Run vllm-project/vllm-ascend test
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env:
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VLLM_WORKER_MULTIPROC_METHOD: spawn
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VLLM_USE_MODELSCOPE: True
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PYTORCH_NPU_ALLOC_CONF: max_split_size_mb:256
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if: ${{ inputs.type == 'light' }}
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run: |
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pytest -sv tests/e2e/singlecard/test_aclgraph.py
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pytest -sv tests/e2e/singlecard/test_quantization.py
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pytest -sv tests/e2e/singlecard/test_vlm.py::test_multimodal_vl
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- name: Run e2e test
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env:
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VLLM_WORKER_MULTIPROC_METHOD: spawn
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VLLM_USE_MODELSCOPE: True
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PYTORCH_NPU_ALLOC_CONF: max_split_size_mb:256
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if: ${{ inputs.type == 'full' }}
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run: |
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# We found that if running aclgraph tests in batch, it will cause AclmdlRICaptureBegin error. So we run
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# the test separately.
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pytest -sv tests/e2e/singlecard/test_aclgraph.py
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pytest -sv tests/e2e/singlecard/test_aclgraph_mem.py
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pytest -sv tests/e2e/singlecard/test_ascend_scheduler.py
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pytest -sv tests/e2e/singlecard/test_bge_model.py
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pytest -sv tests/e2e/singlecard/test_camem.py
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pytest -sv tests/e2e/singlecard/test_chunked.py
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pytest -sv tests/e2e/singlecard/test_embedding.py
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pytest -sv tests/e2e/singlecard/test_embedding_aclgraph.py
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pytest -sv tests/e2e/singlecard/test_guided_decoding.py
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pytest -sv tests/e2e/singlecard/test_ilama_lora.py
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pytest -sv tests/e2e/singlecard/test_profile_execute_duration.py
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pytest -sv tests/e2e/singlecard/test_quantization.py
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pytest -sv tests/e2e/singlecard/test_sampler.py
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pytest -sv tests/e2e/singlecard/test_vlm.py
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# ------------------------------------ v1 spec decode test ------------------------------------ #
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pytest -sv tests/e2e/singlecard/spec_decode_v1/test_v1_mtp_correctness.py
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pytest -sv tests/e2e/singlecard/spec_decode_v1/test_v1_mtp_torchair_correctness.py
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# Fix me: OOM error
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#pytest -sv tests/e2e/singlecard/spec_decode_v1/test_v1_spec_decode.py
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pytest -sv tests/e2e/singlecard/ops/
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e2e-2-cards:
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name: multicard
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runs-on: ${{ inputs.runner }}-2
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container:
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image: ${{ inputs.image }}
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env:
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VLLM_LOGGING_LEVEL: ERROR
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VLLM_USE_MODELSCOPE: True
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steps:
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- name: Check npu and CANN info
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run: |
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npu-smi info
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cat /usr/local/Ascend/ascend-toolkit/latest/"$(uname -i)"-linux/ascend_toolkit_install.info
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- name: Config mirrors
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run: |
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sed -Ei 's@(ports|archive).ubuntu.com@cache-service.nginx-pypi-cache.svc.cluster.local:8081@g' /etc/apt/sources.list
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pip config set global.index-url http://cache-service.nginx-pypi-cache.svc.cluster.local/pypi/simple
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pip config set global.trusted-host cache-service.nginx-pypi-cache.svc.cluster.local
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apt-get update -y
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apt install git -y
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- name: Checkout vllm-project/vllm-ascend repo
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uses: actions/checkout@v4
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- name: Install system dependencies
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run: |
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apt-get -y install `cat packages.txt`
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apt-get -y install gcc g++ cmake libnuma-dev
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- name: Checkout vllm-project/vllm repo
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uses: actions/checkout@v4
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with:
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repository: vllm-project/vllm
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ref: ${{ inputs.vllm }}
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path: ./vllm-empty
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fetch-depth: 1
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- name: Install vllm-project/vllm from source
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working-directory: ./vllm-empty
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run: |
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VLLM_TARGET_DEVICE=empty pip install -e .
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- name: Install vllm-project/vllm-ascend
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env:
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PIP_EXTRA_INDEX_URL: https://mirrors.huaweicloud.com/ascend/repos/pypi
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run: |
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pip install -r requirements-dev.txt
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pip install -v -e .
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- name: Run vllm-project/vllm-ascend test (light)
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env:
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VLLM_WORKER_MULTIPROC_METHOD: spawn
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VLLM_USE_MODELSCOPE: True
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if: ${{ inputs.type == 'light' }}
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run: |
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pytest -sv tests/e2e/multicard/test_qwen3_moe.py::test_models_distributed_Qwen3_MOE_TP2_WITH_EP
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- name: Run vllm-project/vllm-ascend test (full)
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env:
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VLLM_WORKER_MULTIPROC_METHOD: spawn
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VLLM_USE_MODELSCOPE: True
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if: ${{ inputs.type == 'full' }}
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run: |
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pytest -sv tests/e2e/multicard/test_data_parallel.py
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pytest -sv tests/e2e/multicard/test_expert_parallel.py
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# FixMe
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#pytest -sv tests/e2e/multicard/test_external_launcher.py
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pytest -sv tests/e2e/multicard/test_single_request_aclgraph.py
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pytest -sv tests/e2e/multicard/test_fused_moe_allgather_ep.py
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pytest -sv tests/e2e/multicard/test_ilama_lora_tp2.py
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# To avoid oom, we need to run the test in a single process.
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pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_QwQ
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pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_DeepSeek_multistream_moe
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pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_Qwen3_W8A8
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pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_Qwen3_W4A8DYNAMIC_new_version
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pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_Qwen3_W4A8DYNAMIC_old_version
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pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_DeepSeek_W4A8DYNAMIC
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pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_sp_for_qwen3_moe
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pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_Qwen_Dense_with_flashcomm_v1
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pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_Qwen_Dense_with_prefetch_mlp_weight
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pytest -sv tests/e2e/multicard/test_pipeline_parallel.py
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pytest -sv tests/e2e/multicard/test_prefix_caching.py
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pytest -sv tests/e2e/multicard/test_qwen3_moe.py
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pytest -sv tests/e2e/multicard/test_torchair_graph_mode.py
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