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[Refactor] Migrate profiler config from env vars to explicit ProfilerConfig (#5928)

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### What this PR does / why we need it?

Migrate the torch profiler configuration from deprecated environment
variables (`VLLM_TORCH_PROFILER_DIR`, `VLLM_TORCH_PROFILER_WITH_STACK`,
`VLLM_TORCH_PROFILER_WITH_PROFILE_MEMORY`) to the explicit
`ProfilerConfig` object, aligning with vLLM's configuration best
practices.
The profiler environment variable approach is deprecated in vLLM and
will be removed in v0.14.0 or v1.0.0.

### Does this PR introduce _any_ user-facing change?
yes, for deverlopers who want to fetch profiler, he should use `--profiler-config` instead of `VLLM_TORCH_PROFILER_DIR`
### How was this patch tested?

- vLLM version: v0.13.0
- vLLM main:
11b6af5280

Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
This commit is contained in:
meihanc
2026-01-19 09:27:55 +08:00
committed by GitHub
parent bc1f6713e7
commit 9cad1a8349
3 changed files with 68 additions and 38 deletions
Download Patch File Download Diff File Expand all files Collapse all files

27
docs/source/tutorials/DeepSeek-V3.2.md
View File

@@ -278,9 +278,6 @@ Before you start, please
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=256
export VLLM_TORCH_PROFILER_DIR="./vllm_profile"
export VLLM_TORCH_PROFILER_WITH_STACK=0
export ASCEND_AGGREGATE_ENABLE=1
export ASCEND_TRANSPORT_PRINT=1
export ACL_OP_INIT_MODE=1
@@ -302,6 +299,10 @@ Before you start, please
--tensor-parallel-size $7 \
--enable-expert-parallel \
--speculative-config '{"num_speculative_tokens": 2, "method":"deepseek_mtp"}' \
--profiler-config \
'{"profiler": "torch",
"torch_profiler_dir": "./vllm_profile",
"torch_profiler_with_stack": false}' \
--seed 1024 \
--served-model-name dsv3 \
--max-model-len 68000 \
@@ -351,9 +352,6 @@ Before you start, please
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=256
export VLLM_TORCH_PROFILER_DIR="./vllm_profile"
export VLLM_TORCH_PROFILER_WITH_STACK=0
export ASCEND_AGGREGATE_ENABLE=1
export ASCEND_TRANSPORT_PRINT=1
export ACL_OP_INIT_MODE=1
@@ -376,6 +374,10 @@ Before you start, please
--tensor-parallel-size $7 \
--enable-expert-parallel \
--speculative-config '{"num_speculative_tokens": 2, "method":"deepseek_mtp"}' \
--profiler-config \
'{"profiler": "torch",
"torch_profiler_dir": "./vllm_profile",
"torch_profiler_with_stack": false}' \
--seed 1024 \
--served-model-name dsv3 \
--max-model-len 68000 \
@@ -426,8 +428,6 @@ Before you start, please
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=256
export VLLM_TORCH_PROFILER_DIR="./vllm_profile"
export VLLM_TORCH_PROFILER_WITH_STACK=0
export ASCEND_AGGREGATE_ENABLE=1
export ASCEND_TRANSPORT_PRINT=1
@@ -452,6 +452,10 @@ Before you start, please
--tensor-parallel-size $7 \
--enable-expert-parallel \
--speculative-config '{"num_speculative_tokens": 2, "method":"deepseek_mtp"}' \
--profiler-config \
'{"profiler": "torch",
"torch_profiler_dir": "./vllm_profile",
"torch_profiler_with_stack": false}' \
--seed 1024 \
--served-model-name dsv3 \
--max-model-len 68000 \
@@ -504,9 +508,6 @@ Before you start, please
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=256
export VLLM_TORCH_PROFILER_DIR="./vllm_profile"
export VLLM_TORCH_PROFILER_WITH_STACK=0
export ASCEND_AGGREGATE_ENABLE=1
export ASCEND_TRANSPORT_PRINT=1
export ACL_OP_INIT_MODE=1
@@ -530,6 +531,10 @@ Before you start, please
--tensor-parallel-size $7 \
--enable-expert-parallel \
--speculative-config '{"num_speculative_tokens": 2, "method":"deepseek_mtp"}' \
--profiler-config \
'{"profiler": "torch",
"torch_profiler_dir": "./vllm_profile",
"torch_profiler_with_stack": false}' \
--seed 1024 \
--served-model-name dsv3 \
--max-model-len 68000 \

63
tests/ut/worker/test_worker_v1.py
View File

@@ -2,7 +2,7 @@ import unittest
from unittest.mock import MagicMock, patch
import torch
from vllm.config import CacheConfig, ModelConfig, ParallelConfig, VllmConfig
from vllm.config import CacheConfig, ModelConfig, ParallelConfig, ProfilerConfig, VllmConfig
from tests.ut.base import TestBase
from vllm_ascend.utils import vllm_version_is
@@ -311,26 +311,34 @@ class TestNPUWorker(TestBase):
self.assertIn("Profiler is not enabled", str(cm.exception))
@patch("vllm_ascend.worker.worker.envs_vllm")
@patch("vllm_ascend.worker.worker.envs_ascend")
def test_profile_and_msmonitor_both_enabled_raises_error(
self, mock_envs_vllm, mock_envs_ascend):
self, mock_envs_ascend):
"""Test profile method raises exception when both profiler and msmonitor are enabled"""
from vllm_ascend.worker.worker import NPUWorker
mock_envs_vllm.VLLM_TORCH_PROFILER_DIR = "/path/to/traces"
mock_envs_ascend.MSMONITOR_USE_DAEMON = 1
# Create profiler config object
profiler_config = ProfilerConfig(
profiler="torch",
torch_profiler_dir="/path/to/traces"
)
vllm_config_mock = MagicMock()
vllm_config_mock.profiler_config = profiler_config
# Create worker mock
with patch.object(NPUWorker, "__init__", lambda x, **kwargs: None):
worker = NPUWorker()
worker.vllm_config = vllm_config_mock
# Test should raise exception
with self.assertRaises(RuntimeError) as cm:
_ = worker._init_profiler()
self.assertIn(
"MSMONITOR_USE_DAEMON and VLLM_TORCH_PROFILER_DIR cannot be both set at the same time.",
"MSMONITOR_USE_DAEMON and torch profiler cannot be both enabled at the same time.",
str(cm.exception))
def test_lora_methods(self):
@@ -413,7 +421,6 @@ class TestNPUWorker(TestBase):
mock_model_runner._dummy_run.assert_called_once_with(
num_tokens=mock_decode_token_per_req, uniform_decode=True)
@patch("vllm_ascend.worker.worker.envs_vllm")
@patch("vllm_ascend.worker.worker.logger")
@patch("torch_npu.profiler._ExperimentalConfig")
@patch("torch_npu.profiler.profile")
@@ -432,15 +439,20 @@ class TestNPUWorker(TestBase):
mock_profile,
mock_experimental_config,
mock_logger,
mock_envs_vllm,
):
"""Test _init_profiler method - profiler enabled case with stack and memory profiling enabled"""
from vllm_ascend.worker.worker import NPUWorker
# Set environment variables to enable profiler
mock_envs_vllm.VLLM_TORCH_PROFILER_DIR = "/path/to/traces"
mock_envs_vllm.VLLM_TORCH_PROFILER_WITH_STACK = True
mock_envs_vllm.VLLM_TORCH_PROFILER_WITH_PROFILE_MEMORY = True
# Create profiler config object
profiler_config = ProfilerConfig(
profiler="torch",
torch_profiler_dir="/path/to/traces",
torch_profiler_with_stack=True,
torch_profiler_with_memory=True
)
vllm_config_mock = MagicMock()
vllm_config_mock.profiler_config = profiler_config
# Set enum mocks
mock_export_type.Text = "Text"
@@ -460,6 +472,7 @@ class TestNPUWorker(TestBase):
# Create worker mock
with patch.object(NPUWorker, "__init__", lambda x, **kwargs: None):
worker = NPUWorker()
worker.vllm_config = vllm_config_mock
# Test _init_profiler
result = worker._init_profiler()
@@ -511,17 +524,23 @@ class TestNPUWorker(TestBase):
# Verify return value
self.assertEqual(result, mock_profiler_instance)
@patch("vllm_ascend.worker.worker.envs_vllm")
def test_init_profiler_disabled(self, mock_envs_vllm):
def test_init_profiler_disabled(self):
"""Test _init_profiler method - profiler disabled case"""
from vllm_ascend.worker.worker import NPUWorker
# Set environment variable to disable profiler
mock_envs_vllm.VLLM_TORCH_PROFILER_DIR = None
# Create profiler config object with profiler disabled
profiler_config = ProfilerConfig(
profiler=None,
torch_profiler_dir=""
)
vllm_config_mock = MagicMock()
vllm_config_mock.profiler_config = profiler_config
# Create worker mock
with patch.object(NPUWorker, "__init__", lambda x, **kwargs: None):
worker = NPUWorker()
worker.vllm_config = vllm_config_mock
# Test _init_profiler
result = worker._init_profiler()
@@ -529,17 +548,23 @@ class TestNPUWorker(TestBase):
# Verify returns None
self.assertIsNone(result)
@patch("vllm_ascend.worker.worker.envs_vllm")
def test_init_profiler_empty_dir(self, mock_envs_vllm):
def test_init_profiler_empty_dir(self):
"""Test _init_profiler method - empty directory string case"""
from vllm_ascend.worker.worker import NPUWorker
# Set environment variable to empty string
mock_envs_vllm.VLLM_TORCH_PROFILER_DIR = ""
# Create profiler config object with empty dir
profiler_config = ProfilerConfig(
profiler="torch",
torch_profiler_dir=""
)
vllm_config_mock = MagicMock()
vllm_config_mock.profiler_config = profiler_config
# Create worker mock
with patch.object(NPUWorker, "__init__", lambda x, **kwargs: None):
worker = NPUWorker()
worker.vllm_config = vllm_config_mock
# Test _init_profiler
result = worker._init_profiler()

16
vllm_ascend/worker/worker.py
View File

@@ -489,14 +489,15 @@ class NPUWorker(WorkerBase):
ensure_ec_transfer_initialized(self.vllm_config)
def _init_profiler(self):
# Torch profiler. Enabled and configured through env vars:
# VLLM_TORCH_PROFILER_DIR=/path/to/save/trace
if envs_vllm.VLLM_TORCH_PROFILER_DIR:
# Torch profiler. Enabled through profiler_config:
# --profiler-config.profiler=torch --profiler-config.torch_profiler_dir=/path/to/save/trace
profiler_config = self.vllm_config.profiler_config
if profiler_config.profiler == "torch" and profiler_config.torch_profiler_dir:
if envs_ascend.MSMONITOR_USE_DAEMON:
raise RuntimeError(
"MSMONITOR_USE_DAEMON and VLLM_TORCH_PROFILER_DIR cannot be both set at the same time."
"MSMONITOR_USE_DAEMON and torch profiler cannot be both enabled at the same time."
)
torch_profiler_trace_dir = envs_vllm.VLLM_TORCH_PROFILER_DIR
torch_profiler_trace_dir = profiler_config.torch_profiler_dir
logger.info("Profiling enabled. Traces will be saved to: %s",
torch_profiler_trace_dir)
@@ -517,9 +518,8 @@ class NPUWorker(WorkerBase):
torch_npu.profiler.ProfilerActivity.CPU,
torch_npu.profiler.ProfilerActivity.NPU,
],
with_stack=envs_vllm.VLLM_TORCH_PROFILER_WITH_STACK,
profile_memory=envs_vllm.\
VLLM_TORCH_PROFILER_WITH_PROFILE_MEMORY,
with_stack=profiler_config.torch_profiler_with_stack,
profile_memory=profiler_config.torch_profiler_with_memory,
with_modules=False,
experimental_config=experimental_config,
on_trace_ready=torch_npu.profiler.tensorboard_trace_handler(