Fix offline example profiler configuration

Signed-off-by: hsliuustc0106 <liuhongsheng4@huawei.com>

examples/offline_inference/qwen2_5_omni/end2end.py

@@ -5,10 +5,11 @@ This example shows how to use vLLM-Omni for running offline inference
 with the correct prompt format on Qwen2.5-Omni
 """
 
+import argparse
 import json
 import os
 import time
-from typing import NamedTuple
+from typing import Any, NamedTuple
 
 import numpy as np
 import soundfile as sf
@@ -31,6 +32,16 @@ class QueryResult(NamedTuple):
     limit_mm_per_prompt: dict[str, int]
 
 
+def parse_profiler_config(value: str) -> dict[str, Any]:
+    try:
+        config = json.loads(value)
+    except json.JSONDecodeError as e:
+        raise argparse.ArgumentTypeError(f"--profiler-config must be valid JSON: {e}") from e
+    if not isinstance(config, dict):
+        raise argparse.ArgumentTypeError("--profiler-config must be a JSON object")
+    return config
+
+
 # NOTE: The default `max_num_seqs` and `max_model_len` may result in OOM on
 # lower-end GPUs.
 # Unless specified, these settings have been tested to work on a single L4.
@@ -378,11 +389,11 @@ def main(args):
         for i, prompt in enumerate(prompts):
             prompt["modalities"] = output_modalities
 
-    profiler_enabled = bool(os.getenv("VLLM_TORCH_PROFILER_DIR"))
+    profiler_enabled = args.profiler_config is not None
     if profiler_enabled and hasattr(omni, "start_profile"):
         omni.start_profile(stages=[0])
     elif profiler_enabled:
-        print("[Warn] VLLM_TORCH_PROFILER_DIR is set, but current engine does not support profiler controls.")
+        print("[Warn] --profiler-config was provided, but current engine does not support profiler controls.")
     omni_generator = omni.generate(prompts, sampling_params_list, py_generator=args.py_generator)
 
     # Determine output directory: prefer --output-dir; fallback to --output-wav
@@ -458,6 +469,12 @@ def parse_args():
         default=False,
         help="Enable writing detailed statistics (default: disabled)",
     )
+    parser.add_argument(
+        "--profiler-config",
+        type=parse_profiler_config,
+        default=None,
+        help='JSON profiler config for torch/cuda profiling, e.g. \'{"profiler":"torch","torch_profiler_dir":"./perf"}\'.',
+    )
     parser.add_argument(
         "--stage-init-timeout",
         type=int,

examples/offline_inference/text_to_speech/cosyvoice3/end2end.py

@@ -1,9 +1,11 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import argparse
+import json
 import os
 import urllib.request
 from pathlib import Path
+from typing import Any
 
 import numpy as np
 import soundfile as sf
@@ -19,6 +21,16 @@ from vllm_omni.transformers_utils.configs.cosyvoice3 import CosyVoice3Config
 ZERO_SHOT_PROMPT_URL = "https://raw.githubusercontent.com/FunAudioLLM/CosyVoice/main/asset/zero_shot_prompt.wav"
 
 
+def parse_profiler_config(value: str) -> dict[str, Any]:
+    try:
+        config = json.loads(value)
+    except json.JSONDecodeError as e:
+        raise argparse.ArgumentTypeError(f"--profiler-config must be valid JSON: {e}") from e
+    if not isinstance(config, dict):
+        raise argparse.ArgumentTypeError("--profiler-config must be a JSON object")
+    return config
+
+
 def _default_ref_audio() -> str:
     # Download the upstream zero_shot_prompt.wav into the current dir
     dest = Path("zero_shot_prompt.wav")
@@ -45,6 +57,12 @@ def run_e2e():
         help="Override the deploy config path. If unset, auto-loads "
         "vllm_omni/deploy/cosyvoice3.yaml based on the HF model_type.",
     )
+    parser.add_argument(
+        "--profiler-config",
+        type=parse_profiler_config,
+        default=None,
+        help='JSON profiler config for torch/cuda profiling, e.g. \'{"profiler":"torch","torch_profiler_dir":"./perf"}\'.',
+    )
     parser.add_argument("--text", type=str, default="Hello, this is a test of the CosyVoice system capability.")
     parser.add_argument(
         "--prompt-text",
@@ -79,6 +97,7 @@ def run_e2e():
         deploy_config=args.deploy_config,
         tokenizer=args.tokenizer,
         log_stats=True,
+        profiler_config=args.profiler_config,
     )
 
     sampling_cfg = {"top_p": 0.8, "top_k": 25, "eos_token_id": 6561 + 1}
@@ -149,8 +168,8 @@ def run_e2e():
 
     sampling_params_list = [gpt_sampling, s2mel_sampling]
 
-    # Start profiling (requires VLLM_TORCH_PROFILER_DIR env var)
-    if os.environ.get("VLLM_TORCH_PROFILER_DIR"):
+    profiler_enabled = args.profiler_config is not None
+    if profiler_enabled:
         print("Starting profiler...")
         omni.start_profile()
 
@@ -158,7 +177,7 @@ def run_e2e():
     outputs = list(omni.generate(prompts, sampling_params_list=sampling_params_list[:2]))
 
     # Stop profiling and get results
-    if os.environ.get("VLLM_TORCH_PROFILER_DIR"):
+    if profiler_enabled:
         print("Stopping profiler...")
         profile_results = omni.stop_profile()
         print(f"Profile traces saved to: {profile_results}")

tests/docs/test_offline_profiler_config.py

@@ -0,0 +1,23 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+
+from pathlib import Path
+
+import pytest
+
+pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
+
+_REPO_ROOT = Path(__file__).resolve().parents[2]
+_EXAMPLES = (
+    "examples/offline_inference/text_to_speech/cosyvoice3/end2end.py",
+    "examples/offline_inference/qwen2_5_omni/end2end.py",
+)
+
+
+@pytest.mark.parametrize("relative_path", _EXAMPLES)
+def test_offline_examples_use_typed_profiler_config(relative_path: str):
+    source = (_REPO_ROOT / relative_path).read_text(encoding="utf-8")
+
+    assert "--profiler-config" in source
+    assert "profiler_enabled = args.profiler_config is not None" in source
+    assert "VLLM_TORCH_PROFILER_DIR" not in source