[Refactor] Share offline profiler argument parser

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

examples/offline_inference/qwen2_5_omni/end2end.py

@@ -21,6 +21,7 @@ from vllm.multimodal.media.audio import load_audio
 from vllm.sampling_params import SamplingParams
 
 from vllm_omni.entrypoints.omni import Omni
+from vllm_omni.utils.profiler import add_profiler_config_arg
 from vllm_omni.utils.tracking_parser import TrackingArgumentParser
 
 SEED = 42
@@ -325,6 +326,7 @@ def main(args):
     else:
         query_result = query_func()
     args.quantization_config = quantization_config
+    # ``vars(args)`` below forwards profiler_config to Omni.
     omni_kwargs = vars(args).copy()
     # Override CLI --model with the derived model_name.
     omni_kwargs["model"] = model_name
@@ -378,11 +380,11 @@ 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 +460,7 @@ def parse_args():
         default=False,
         help="Enable writing detailed statistics (default: disabled)",
     )
+    add_profiler_config_arg(parser)
     parser.add_argument(
         "--stage-init-timeout",
         type=int,

examples/offline_inference/text_to_speech/cosyvoice3/end2end.py

@@ -14,6 +14,7 @@ from vllm_omni.entrypoints.omni import Omni
 from vllm_omni.model_executor.models.cosyvoice3.tokenizer import get_qwen_tokenizer
 from vllm_omni.model_executor.models.cosyvoice3.utils import extract_text_token
 from vllm_omni.transformers_utils.configs.cosyvoice3 import CosyVoice3Config
+from vllm_omni.utils.profiler import add_profiler_config_arg
 
 # Upstream zero-shot reference clip
 ZERO_SHOT_PROMPT_URL = "https://raw.githubusercontent.com/FunAudioLLM/CosyVoice/main/asset/zero_shot_prompt.wav"
@@ -45,6 +46,7 @@ def run_e2e():
         help="Override the deploy config path. If unset, auto-loads "
         "vllm_omni/deploy/cosyvoice3.yaml based on the HF model_type.",
     )
+    add_profiler_config_arg(parser)
     parser.add_argument("--text", type=str, default="Hello, this is a test of the CosyVoice system capability.")
     parser.add_argument(
         "--prompt-text",
@@ -79,6 +81,7 @@ 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 +152,8 @@ 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 +161,7 @@ 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 "add_profiler_config_arg(parser)" in source
+    assert "profiler_enabled = args.profiler_config is not None" in source
+    assert "VLLM_TORCH_PROFILER_DIR" not in source

vllm_omni/utils/profiler.py

@@ -0,0 +1,37 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+
+from __future__ import annotations
+
+import argparse
+import json
+from typing import Any
+
+
+def parse_json_object(value: str, flag_name: str = "argument") -> dict[str, Any]:
+    """Parse a CLI value as a JSON object, attributing errors to ``flag_name``."""
+    try:
+        config = json.loads(value)
+    except json.JSONDecodeError as e:
+        raise argparse.ArgumentTypeError(f"{flag_name} must be valid JSON: {e}") from e
+    if not isinstance(config, dict):
+        raise argparse.ArgumentTypeError(f"{flag_name} must be a JSON object")
+    return config
+
+
+def parse_profiler_config(value: str) -> dict[str, Any]:
+    """Parse the JSON object passed to ``--profiler-config``."""
+    return parse_json_object(value, flag_name="--profiler-config")
+
+
+def add_profiler_config_arg(parser: argparse.ArgumentParser) -> None:
+    """Add the shared JSON profiler configuration option to ``parser``."""
+    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"}\'.'
+        ),
+    )