[TEST]Add aisbench log and A2 cases (#3841)

### What this PR does / why we need it?
This PR adds 2 more A2 caces which we need to test daily. It also
enhances the logging for aisbench test failures to improve issues
identification
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running the test

- vLLM version: v0.11.0rc3
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.1

---------

Signed-off-by: jiangyunfan1 <jiangyunfan1@h-partners.com>

.github/workflows/vllm_ascend_test_nightly_a2.yaml

@@ -73,6 +73,9 @@ jobs:
           - name: multi-node-deepseek-dp
             config_file_path: tests/e2e/nightly/multi_node/config/models/DeepSeek-R1-W8A8-A2.yaml
             size: 2
+          - name: multi-node-deepseek-dp-torchair
+            config_file_path: tests/e2e/nightly/multi_node/config/models/DeepSeek-R1-W8A8-A2-torchair.yaml
+            size: 2
     uses: ./.github/workflows/_e2e_nightly_multi_node.yaml
     with:
       soc_version: a2

tests/e2e/nightly/models/test_deepseek_r1_0528_w8a8.py

@@ -133,4 +133,7 @@ async def test_models(model: str, mode: str) -> None:
         if mode in ["single", "no_chunkprefill"]:
             return
         # aisbench test
-        run_aisbench_cases(model, port, aisbench_cases)
+        run_aisbench_cases(model,
+                           port,
+                           aisbench_cases,
+                           server_args=server_args)

tests/e2e/nightly/multi_node/config/models/DeepSeep-R1-W8A8-A2-torchair.yaml

@@ -0,0 +1,64 @@
+test_name: "test DeepSeek-R1-W8A8 torchair on A2"
+model: "vllm-ascend/DeepSeek-R1-0528-W8A8"
+num_nodes: 2
+npu_per_node: 8
+env_common:
+  VLLM_USE_MODELSCOPE: true
+  HCCL_BUFFSIZE: 1024
+  SERVER_PORT: 8080
+  OMP_PROC_BIND: false
+  OMP_NUM_THREADS: 10
+
+
+deployment:
+  -
+    server_cmd: >
+      vllm serve vllm-ascend/DeepSeek-R1-0528-W8A8
+      --host 0.0.0.0
+      --port $SERVER_PORT
+      --data-parallel-size 4
+      --data-parallel-size-local 2
+      --data-parallel-address $LOCAL_IP
+      --data-parallel-rpc-port 13399
+      --no-enable-prefix-caching
+      --max-num-seqs 16
+      --tensor-parallel-size 4
+      --max-model-len 36864
+      --max-num-batched-tokens 6000
+      --enable-expert-parallel
+      --trust-remote-code
+      --quantization ascend
+      --gpu-memory-utilization 0.9
+      --speculative-config '{"num_speculative_tokens": 1, "method":"deepseek_mtp"}'
+      --additional-config '{"ascend_scheduler_config":{"enabled":false},"torchair_graph_config":{"enabled":true,"enable_multistream_moe":true},"chunked_prefill_for_mla":true,"enable_weight_nz_layout":true}'
+
+  -
+    server_cmd: >
+      vllm serve vllm-ascend/DeepSeek-R1-0528-W8A8
+      --headless
+      --data-parallel-size 4
+      --data-parallel-rpc-port 13399
+      --data-parallel-size-local 2
+      --data-parallel-start-rank 2
+      --data-parallel-address $MASTER_IP
+      --no-enable-prefix-caching
+      --max-num-seqs 16
+      --tensor-parallel-size 4
+      --max-model-len 36864
+      --max-num-batched-tokens 6000
+      --enable-expert-parallel
+      --trust-remote-code
+      --quantization ascend
+      --gpu-memory-utilization 0.9
+      --speculative-config '{"num_speculative_tokens": 1, "method":"deepseek_mtp"}'
+      --additional-config '{"ascend_scheduler_config":{"enabled":false},"torchair_graph_config":{"enabled":true,"enable_multistream_moe":true},"chunked_prefill_for_mla":true,"enable_weight_nz_layout":true}'
+benchmarks:
+  acc:
+    case_type: accuracy
+    dataset_path: vllm-ascend/gsm8k
+    request_conf: vllm_api_general_chat
+    dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_chat_prompt
+    max_out_len: 32768
+    batch_size: 512
+    baseline: 95
+    threshold: 5

tests/e2e/nightly/multi_node/config/models/DeepSeep-R1-W8A8-A2.yaml

@@ -30,7 +30,7 @@ deployment:
       --quantization ascend
       --gpu-memory-utilization 0.9
       --enforce-eager
-      --speculative-config '{"num_speculative_tokens": 1, "method":"deepseek_mtp"}' \
+      --speculative-config '{"num_speculative_tokens": 1, "method":"deepseek_mtp"}'
       --additional-config '{"ascend_scheduler_config":{"enabled":false},"chunked_prefill_for_mla":true,"enable_weight_nz_layout":true}'
 
   -
@@ -52,6 +52,6 @@ deployment:
       --quantization ascend
       --gpu-memory-utilization 0.9
       --enforce-eager
-      --speculative-config '{"num_speculative_tokens": 1, "method":"deepseek_mtp"}' \
+      --speculative-config '{"num_speculative_tokens": 1, "method":"deepseek_mtp"}'
       --additional-config '{"ascend_scheduler_config":{"enabled":false},"chunked_prefill_for_mla":true,"enable_weight_nz_layout":true}'
 benchmarks:

tests/e2e/nightly/multi_node/test_multi_node.py

@@ -117,9 +117,7 @@ async def test_multi_node() -> None:
             if config.is_master:
                 port = proxy_port if disaggregated_prefill else server_port
                 # aisbench test
-                if acc_cmd:
-                    run_aisbench_cases(local_model_path, port, acc_cmd)
-                if perf_cmd:
-                    run_aisbench_cases(local_model_path, port, perf_cmd)
+                aisbench_cases = [acc_cmd, perf_cmd]
+                run_aisbench_cases(local_model_path, port, aisbench_cases)
             else:
                 remote_server.hang_until_terminated()

tools/aisbench.py

@@ -16,6 +16,7 @@
 #
 import hashlib
 import json
+import logging
 import os
 import re
 import subprocess
@@ -188,8 +189,8 @@ class AisbenchRunner:
                                             line).group(1)
                 return
             if "ERROR" in line:
-                raise RuntimeError(
-                    "Some errors happen to Aisbench task.") from None
+                error_msg = f"Some errors happened to Aisbench runtime, the first error is {line}"
+                raise RuntimeError(error_msg) from None
 
     def _wait_for_task(self):
         self._wait_for_exp_folder()
@@ -201,8 +202,8 @@ class AisbenchRunner:
                 self.result_line = line
                 return
             if "ERROR" in line:
-                raise RuntimeError(
-                    "Some errors happen to Aisbench task.") from None
+                error_msg = f"Some errors happened to Aisbench runtime, the first error is {line}"
+                raise RuntimeError(error_msg) from None
 
     def _get_result_performance(self):
         result_dir = re.search(r'Performance Result files locate in (.*)',
@@ -237,12 +238,12 @@ class AisbenchRunner:
         assert self.baseline - self.threshold <= acc_value <= self.baseline + self.threshold, f"Accuracy verification failed. The accuracy of {self.dataset_path} is {acc_value}, which is not within {self.threshold} relative to baseline {self.baseline}."
 
 
-def run_aisbench_cases(model, port, aisbench_cases):
-    if isinstance(aisbench_cases, dict):
-        aisbench_cases = [aisbench_cases]
+def run_aisbench_cases(model, port, aisbench_cases, server_args=""):
     aisbench_results = []
     aisbench_errors = []
     for aisbench_case in aisbench_cases:
+        if not aisbench_case:
+            continue
         try:
             with AisbenchRunner(model, port, aisbench_case) as aisbench:
                 aisbench_results.append(aisbench.result)
@@ -251,9 +252,10 @@ def run_aisbench_cases(model, port, aisbench_cases):
             aisbench_errors.append([aisbench_case, e])
             print(e)
     for failed_case, error_info in aisbench_errors:
-        print(
-            f"The following aisbench case failed: {failed_case}, reason is {error_info}."
-        )
+        error_msg = f"The following aisbench case failed: {failed_case}, reason is {error_info}"
+        if server_args:
+            error_msg += f"\nserver_args are {server_args}"
+        logging.error(error_msg)
     assert not aisbench_errors, "some aisbench cases failed, info were shown above."
     return aisbench_results