### What this PR does / why we need it? We need to **observe the time consumed in each stage of inference (including pre-processing, model forward, etc.), without any performance loss**. Therefore, we use the event timestamp mechanism of the NPU to mark any stage during the execution of the NPU device (this marking operation is executed asynchronously, with no performance loss). Additionally, we provide a blocking synchronization API `pop_captured_sync` to be called at an appropriate time, to print the time consumed in all observed stages. **model_runner_v1.py file only changed 5 lines, all of which were `ProfileExecuteDuration()` calls, and nothing else was changed, while more changes were showed due to the alignment issue.** ### Does this PR introduce _any_ user-facing change? Use env `VLLM_MODEL_EXECUTE_TIME_OBSERVE `to enable this feature ### How was this patch tested? Tested in deepseek model,Print like this: ``` 5691:(IntegratedWorker pid=1502285) Profile execute duration [Decode]: [post process]:14.17ms [prepare input and forward]:9.57ms [forward]:4.14ms 5695:(IntegratedWorker pid=1502285) Profile execute duration [Decode]: [post process]:14.29ms [prepare input and forward]:10.19ms [forward]:4.14ms 5697:(IntegratedWorker pid=1502343) Profile execute duration [Decode]: [post process]:14.81ms [prepare input and forward]:10.29ms [forward]:3.99ms 5701:(IntegratedWorker pid=1502343) Profile execute duration [Decode]: [post process]:14.10ms [prepare input and forward]:10.62ms [forward]:4.33ms 5705:(IntegratedWorker pid=1502343) Profile execute duration [Decode]: [post process]:14.65ms [prepare input and forward]:9.58ms [forward]:4.20ms 5709:(IntegratedWorker pid=1502343) Profile execute duration [Decode]: [post process]:14.43ms [prepare input and forward]:9.88ms [forward]:4.20ms 5711:(IntegratedWorker pid=1502401) Profile execute duration [Decode]: [post process]:14.89ms [prepare input and forward]:10.49ms [forward]:4.19ms 5715:(IntegratedWorker pid=1502401) Profile execute duration [Decode]: [post process]:14.14ms [prepare input and forward]:11.21ms [forward]:4.18ms 5719:(IntegratedWorker pid=1502401) Profile execute duration [Decode]: [post process]:14.71ms [prepare input and forward]:10.15ms [forward]:4.42ms 5723:(IntegratedWorker pid=1502401) Profile execute duration [Decode]: [post process]:14.62ms [prepare input and forward]:10.31ms [forward]:4.25ms 5725:(IntegratedWorker pid=1502462) Profile execute duration [Decode]: [post process]:14.12ms [prepare input and forward]:10.33ms [forward]:4.24ms 5729:(IntegratedWorker pid=1502462) Profile execute duration [Decode]: [post process]:14.58ms [prepare input and forward]:10.85ms [forward]:4.32ms 5733:(IntegratedWorker pid=1502462) Profile execute duration [Decode]: [post process]:14.32ms [prepare input and forward]:9.79ms [forward]:4.28ms 5737:(IntegratedWorker pid=1502462) Profile execute duration [Decode]: [post process]:15.06ms [prepare input and forward]:9.89ms [forward]:4.32ms 5739:(IntegratedWorker pid=1502524) Profile execute duration [Decode]: [post process]:14.62ms [prepare input and forward]:10.48ms [forward]:4.27ms 5743:(IntegratedWorker pid=1502524) Profile execute duration [Decode]: [post process]:14.60ms [prepare input and forward]:10.71ms [forward]:4.61ms 5747:(IntegratedWorker pid=1502524) Profile execute duration [Decode]: [post process]:14.21ms [prepare input and forward]:10.10ms [forward]:4.52ms 5751:(IntegratedWorker pid=1502524) Profile execute duration [Decode]: [post process]:15.03ms [prepare input and forward]:10.00ms [forward]:4.42ms ``` --------- Signed-off-by: depeng1994 <depengzhang@foxmail.com>
90 lines
3.1 KiB
Python
90 lines
3.1 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# This file is a part of the vllm-ascend project.
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#
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# This file is mainly Adapted from vllm-project/vllm/vllm/envs.py
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# Copyright 2023 The vLLM team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import os
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from typing import Any, Callable, Dict
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# The begin-* and end* here are used by the documentation generator
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# to extract the used env vars.
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# begin-env-vars-definition
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env_variables: Dict[str, Callable[[], Any]] = {
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# max compile thread num
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"MAX_JOBS":
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lambda: os.getenv("MAX_JOBS", None),
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"CMAKE_BUILD_TYPE":
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lambda: os.getenv("CMAKE_BUILD_TYPE"),
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"COMPILE_CUSTOM_KERNELS":
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lambda: bool(int(os.getenv("COMPILE_CUSTOM_KERNELS", "1"))),
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"VLLM_ENABLE_MC2":
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lambda: bool(int(os.getenv("VLLM_ENABLE_MC2", '0'))),
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"VLLM_ASCEND_ENABLE_TOPK_OPTIMZE":
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lambda: bool(int(os.getenv("VLLM_ASCEND_ENABLE_TOPK_OPTIMZE", '0'))),
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"USING_LCCL_COM":
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lambda: bool(int(os.getenv("USING_LCCL_COM", '0'))),
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"SOC_VERSION":
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lambda: os.getenv("SOC_VERSION", "ASCEND910B1"),
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# If set, vllm-ascend will print verbose logs during compilation
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"VERBOSE":
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lambda: bool(int(os.getenv('VERBOSE', '0'))),
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"ASCEND_HOME_PATH":
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lambda: os.getenv("ASCEND_HOME_PATH", None),
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"LD_LIBRARY_PATH":
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lambda: os.getenv("LD_LIBRARY_PATH", None),
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# Used for disaggregated prefilling
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"HCCN_PATH":
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lambda: os.getenv("HCCN_PATH", "/usr/local/Ascend/driver/tools/hccn_tool"),
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"HCCL_SO_PATH":
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lambda: os.environ.get("HCCL_SO_PATH", None),
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"PROMPT_DEVICE_ID":
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lambda: os.getenv("PROMPT_DEVICE_ID", None),
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"DECODE_DEVICE_ID":
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lambda: os.getenv("DECODE_DEVICE_ID", None),
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"LLMDATADIST_COMM_PORT":
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lambda: os.getenv("LLMDATADIST_COMM_PORT", "26000"),
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"LLMDATADIST_SYNC_CACHE_WAIT_TIME":
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lambda: os.getenv("LLMDATADIST_SYNC_CACHE_WAIT_TIME", "5000"),
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"CXX_COMPILER":
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lambda: os.getenv("CXX_COMPILER", None),
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"C_COMPILER":
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lambda: os.getenv("C_COMPILER", None),
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"VLLM_VERSION":
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lambda: os.getenv("VLLM_VERSION", None),
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"VLLM_ASCEND_TRACE_RECOMPILES":
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lambda: bool(int(os.getenv("VLLM_ASCEND_TRACE_RECOMPILES", '0'))),
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"VLLM_ASCEND_MODEL_EXECUTE_TIME_OBSERVE":
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lambda: bool(int(os.getenv("VLLM_ASCEND_MODEL_EXECUTE_TIME_OBSERVE", '0'))
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),
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}
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# end-env-vars-definition
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def __getattr__(name: str):
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# lazy evaluation of environment variables
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if name in env_variables:
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return env_variables[name]()
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raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
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def __dir__():
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return list(env_variables.keys())
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