[CI]test qwen3-235B and qwen3-vl-235b nightly

.github/workflows/_e2e_nightly_multi_node.yaml

@@ -101,7 +101,8 @@ jobs:
         - name: Decode kubeconfig from secrets
           run: |
             # Decode and save kubeconfig
-            echo "${{ secrets.KUBECONFIG_B64 }}" | base64 -d > $KUBECONFIG
+            # echo "${{ secrets.KUBECONFIG_B64 }}" | base64 -d > $KUBECONFIG
+            cp /root/.cache/.kube/kubeconfig.yaml $KUBECONFIG 
 
         - name: Checkout code
           uses: actions/checkout@v6

.github/workflows/nightly_test_a3.yaml

@@ -28,7 +28,10 @@ on:
   pull_request: 
     branches:
       - 'main'
-    types: [ labeled ]
+    # types: [ labeled ]
+  push: 
+    branches:
+      - 'main'
 
 # 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.
@@ -44,39 +47,51 @@ concurrency:
 jobs:
   multi-node-tests:
     name: multi-node
-    if: always() && (github.event_name == 'schedule' || github.event_name == 'workflow_dispatch')
+    # if: always() && (github.event_name == 'schedule' || github.event_name == 'workflow_dispatch')
     strategy:
       fail-fast: false
       max-parallel: 1
       matrix:
         test_config:
-          - name: multi-node-deepseek-pd
-            config_file_path: DeepSeek-V3.yaml
-            size: 2
-          - name: multi-node-qwen3-dp
-            config_file_path: Qwen3-235B-A22B.yaml
-            size: 2
-          # - name: multi-node-dpsk-4node-pd
-          #   config_file_path: DeepSeek-R1-W8A8.yaml
-          #   size: 4
-          - name: multi-node-qwenw8a8-2node
-            config_file_path: Qwen3-235B-W8A8.yaml
-            size: 2
-          # - name: multi-node-deepseek-r1-w8a8-eplb
-          #   config_file_path: DeepSeek-R1-W8A8-EPLB.yaml
-          #   size: 4
-          - name: multi-node-qwenw8a8-2node-eplb
-            config_file_path: Qwen3-235B-W8A8-EPLB.yaml
-            size: 2
-          - name: multi-node-dpsk3.2-2node
-            config_file_path: DeepSeek-V3_2-W8A8-A3-dual-nodes.yaml
-            size: 2
-          - name: multi-node-deepseek-r1-w8a8-longseq
-            config_file_path: DeepSeek-R1-W8A8-longseq.yaml
+          # - name: multi-node-deepseek-pd
+          #   config_file_path: DeepSeek-V3.yaml
+          #   size: 2
+          # - name: multi-node-qwen3-dp
+          #   config_file_path: Qwen3-235B-A22B.yaml
+          #   size: 2
+          # # - name: multi-node-dpsk-4node-pd
+          # #   config_file_path: DeepSeek-R1-W8A8.yaml
+          # #   size: 4
+          # - name: multi-node-qwenw8a8-2node
+          #   config_file_path: Qwen3-235B-W8A8.yaml
+          #   size: 2
+          # # - name: multi-node-deepseek-r1-w8a8-eplb
+          # #   config_file_path: DeepSeek-R1-W8A8-EPLB.yaml
+          # #   size: 4
+          # - name: multi-node-qwenw8a8-2node-eplb
+          #   config_file_path: Qwen3-235B-W8A8-EPLB.yaml
+          #   size: 2
+          - name: multi-node-qwen3-vl-235b-a22b
+            config_file_path: Qwen3-VL-235B-A22B-Instruct.yaml
             size: 2
-          - name: multi-node-qwenw8a8-2node-longseq
-            config_file_path: Qwen3-235B-W8A8-longseq.yaml
+          # - name: multi-node-dpsk3.2-2node
+          #   config_file_path: DeepSeek-V3_2-W8A8-A3-dual-nodes.yaml
+          #   size: 2
+          # - name: multi-node-deepseek-r1-w8a8-longseq
+          #   config_file_path: DeepSeek-R1-W8A8-longseq.yaml
+          #   size: 2
+          # - name: multi-node-qwenw8a8-2node-longseq
+          #   config_file_path: Qwen3-235B-W8A8-longseq.yaml
+          #   size: 2
+          - name: multi-node-qwen3-235b-a22b-pd
+            config_file_path: Qwen3-235B-A22B-pd.yaml
             size: 2
+          # - name: multi-node-deepseek-r1-w8a8-longseq
+          #   config_file_path: DeepSeek-R1-W8A8-longseq.yaml
+          #   size: 2
+          # - name: multi-node-qwenw8a8-2node-longseq
+          #   config_file_path: Qwen3-235B-W8A8-longseq.yaml
+          #   size: 2
     uses: ./.github/workflows/_e2e_nightly_multi_node.yaml
     with:
       soc_version: a3

tests/e2e/nightly/multi_node/config/Qwen3-235B-A22B-pd.yaml

@@ -0,0 +1,121 @@
+test_name: "test Qwen3-235B-A22B pd online"
+model: "Qwen/Qwen3-235B-A22B"
+num_nodes: 2
+npu_per_node: 16
+env_common:
+  VLLM_USE_MODELSCOPE: true
+  PYTORCH_NPU_ALLOC_CONF: expandable_segments:True
+  HCCL_BUFFSIZE: 1024
+  HCCL_OP_EXPANSION_MODE: "AIV"
+  OMP_PROC_BIND: false
+  OMP_NUM_THREADS: 1
+  VLLM_ASCEND_ENABLE_FLASHCOMM1: 1
+  VLLM_ASCEND_ENABLE_FUSED_MC2: 2
+  TASK_QUEUE_ENABLE: 1
+  SERVER_PORT: 8080
+
+disaggregated_prefill:
+  enabled: true
+  prefiller_host_index: [0]
+  decoder_host_index: [1]
+
+deployment:
+  -
+    server_cmd: >
+        vllm serve "Qwen/Qwen3-235B-A22B"
+        --host 0.0.0.0
+        --port $SERVER_PORT
+        --data-parallel-size 2
+        --data-parallel-size-local 2
+        --data-parallel-start-rank 0
+        --data-parallel-address $LOCAL_IP
+        --data-parallel-rpc-port 13389
+        --tensor-parallel-size 8
+        --seed 1024
+        --max-num-seqs 32
+        --max-model-len 8192
+        --max-num-batched-tokens 8192
+        --enable-expert-parallel
+        --trust-remote-code
+        --gpu-memory-utilization 0.9
+        --no-enable-prefix-caching
+        --kv-transfer-config
+        '{"kv_connector": "MooncakeConnectorV1",
+        "kv_role": "kv_producer",
+        "kv_port": "30000",
+        "engine_id": "0",
+        "kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
+        "kv_connector_extra_config": {
+                  "use_ascend_direct": true,
+                  "prefill": {
+                          "dp_size": 2,
+                          "tp_size": 8
+                  },
+                  "decode": {
+                          "dp_size": 4,
+                          "tp_size": 4
+                  }
+            }
+        }'
+
+  -
+    server_cmd: >
+        vllm serve "Qwen/Qwen3-235B-A22B"
+        --host 0.0.0.0
+        --port $SERVER_PORT
+        --data-parallel-size 4
+        --data-parallel-size-local 4
+        --data-parallel-start-rank 0
+        --data-parallel-address $LOCAL_IP
+        --data-parallel-rpc-port 13389
+        --tensor-parallel-size 4
+        --seed 1024
+        --max-num-seqs 32
+        --max-model-len 8192
+        --max-num-batched-tokens 8192
+        --enable-expert-parallel
+        --trust-remote-code
+        --gpu-memory-utilization 0.9
+        --no-enable-prefix-caching
+        --compilation-config '{"cudagraph_mode":"FULL_DECODE_ONLY"}'
+        --async-scheduling
+        --kv-transfer-config
+        '{"kv_connector": "MooncakeConnectorV1",
+        "kv_role": "kv_consumer",
+        "kv_port": "30100",
+        "engine_id": "1",
+        "kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
+        "kv_connector_extra_config": {
+                  "use_ascend_direct": true,
+                  "prefill": {
+                          "dp_size": 2,
+                          "tp_size": 8
+                  },
+                  "decode": {
+                          "dp_size": 4,
+                          "tp_size": 4
+                  }
+            }
+        }'
+
+benchmarks:
+  perf:
+    case_type: performance
+    dataset_path: vllm-ascend/GSM8K-in3500-bs2800
+    request_conf: vllm_api_stream_chat
+    dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_str_perf
+    num_prompts: 2800
+    max_out_len: 1500
+    batch_size: 700
+    request_rate: 11.2
+    baseline: 1
+    threshold: 0.97
+  acc:
+    case_type: accuracy
+    dataset_path: vllm-ascend/gsm8k-lite
+    request_conf: vllm_api_general_chat
+    dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_chat_prompt
+    max_out_len: 7680
+    batch_size: 512
+    baseline: 97
+    threshold: 3

tests/e2e/nightly/multi_node/config/Qwen3-VL-235B-A22B-Instruct.yaml

@@ -0,0 +1,108 @@
+test_name: "test qwen3-vl-235b-a22b disaggregated_prefill on A3"
+model: "Qwen/Qwen3-VL-235B-A22B-Instruct"
+num_nodes: 2
+npu_per_node: 16
+env_common:
+  VLLM_USE_MODELSCOPE: true
+  HCCL_BUFFSIZE: 1024
+  SERVER_PORT: 8080
+  OMP_PROC_BIND: false
+  OMP_NUM_THREADS: 1
+  HCCL_OP_EXPANSION_MODE: "AIV"
+  TASK_QUEUE_ENABLE: 1
+  PYTORCH_NPU_ALLOC_CONF: expandable_segments:True
+
+disaggregated_prefill:
+  enabled: true
+  prefiller_host_index: [0]
+  decoder_host_index: [1]
+
+deployment:
+  -
+    server_cmd: >
+      vllm serve "Qwen/Qwen3-VL-235B-A22B-Instruct"
+      --host 0.0.0.0
+      --port $SERVER_PORT
+      --data-parallel-size 2
+      --data-parallel-size-local 2
+      --tensor-parallel-size 8
+      --seed 1024
+      --enable-expert-parallel
+      --max-num-seqs 32
+      --max-model-len 8192
+      --max-num-batched-tokens 8192
+      --trust-remote-code
+      --no-enable-prefix-caching
+      --gpu-memory-utilization 0.9
+      --kv-transfer-config
+      '{"kv_connector": "MooncakeConnectorV1",
+      "kv_role": "kv_producer",
+      "kv_port": "30000",
+      "engine_id": "0",
+      "kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
+      "kv_connector_extra_config": {
+                "prefill": {
+                        "dp_size": 2,
+                        "tp_size": 8
+                },
+                "decode": {
+                        "dp_size": 4,
+                        "tp_size": 4
+                }
+          }
+      }'
+  -
+    server_cmd: >
+      vllm serve "Qwen/Qwen3-VL-235B-A22B-Instruct"
+      --host 0.0.0.0
+      --port $SERVER_PORT
+      --data-parallel-size 4
+      --data-parallel-size-local 4
+      --tensor-parallel-size 4
+      --seed 1024
+      --enable-expert-parallel
+      --max-num-seqs 32
+      --max-model-len 8192
+      --max-num-batched-tokens 8192
+      --trust-remote-code
+      --no-enable-prefix-caching
+      --gpu-memory-utilization 0.9
+      --compilation-config '{"cudagraph_mode":"FULL_DECODE_ONLY"}'
+      --kv-transfer-config
+      '{"kv_connector": "MooncakeConnectorV1",
+      "kv_role": "kv_consumer",
+      "kv_port": "30200",
+      "engine_id": "1",
+      "kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
+      "kv_connector_extra_config": {
+                "prefill": {
+                        "dp_size": 2,
+                        "tp_size": 8
+                },
+                "decode": {
+                        "dp_size": 4,
+                        "tp_size": 4
+                }
+          }
+      }'
+benchmarks:
+  perf:
+    case_type: performance
+    dataset_path: vllm-ascend/textvqa-perf-1080p
+    request_conf: vllm_api_stream_chat
+    dataset_conf: textvqa/textvqa_gen_base64
+    num_prompts: 2800
+    max_out_len: 1500
+    batch_size: 64
+    request_rate: 11.2
+    baseline: 1
+    threshold: 0.97
+  acc:
+    case_type: accuracy
+    dataset_path: vllm-ascend/textvqa-lite
+    request_conf: vllm_api_stream_chat
+    dataset_conf: textvqa/textvqa_gen_base64
+    max_out_len: 7680
+    batch_size: 64
+    baseline: 85
+    threshold: 5

tests/e2e/nightly/multi_node/scripts/run.sh

@@ -157,6 +157,18 @@ kill_npu_processes() {
   sleep 4
 }
 
+upgrade_vllm_ascend_scr() {
+    # Fix me(Potabk): Remove this once our image build use 
+    # The separate architecture build process currently suffers from errors during cross-compilation
+    # causing the image to fail to build correctly. 
+    # This results in the nightly test code not being the latest version.
+    cd "$WORKSPACE/vllm-ascend"
+    #git pull origin main
+    git fetch origin pull/5442/head:pr-5442
+    git checkout pr-5442
+
+}
+
 run_tests_with_log() {
     set +e
     kill_npu_processes
@@ -181,6 +193,7 @@ main() {
     if [[ "$CONFIG_YAML_PATH" == *"DeepSeek-V3_2-Exp-bf16.yaml" ]]; then
         install_extra_components
     fi
+    upgrade_vllm_ascend_scr
     cd "$WORKSPACE/vllm-ascend"
     run_tests_with_log
 }

vllm_ascend/ascend_config.py

@@ -108,8 +108,12 @@ def __init__(self, vllm_config: "VllmConfig"):
                     decode_tp_size = min(decode_tp_size, num_kv_head)
                     self.pd_head_ratio = prefill_tp_size // decode_tp_size
                 except Exception:
-                    raise AssertionError(
-                        "Can not get num_key_value_heads from model_config")
+                    raise ValueError(
+                        "The text_config extracted from the model config does not have "
+                        "`num_key_value_heads` attribute. This indicates a mismatch "
+                        "between the model config and vLLM's expectations. Please "
+                        "ensure that the model config is compatible with vLLM."
+                    )
 
             if self.pd_tp_ratio == 0:
                 raise AssertionError(