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[Misc] Adjust the default profiler configuration (#1097)

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### What this PR does / why we need it?
When profiling, it is often necessary to disable the call stack to
reduce profiling overhead, and adjust the profiler_level to level1 to
obtain more detailed operator and communication information.

Therefore, it is recommended to modify the default profiling
configuration.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
No

Signed-off-by: ApsarasX <apsarax@outlook.com>
This commit is contained in:
ApsarasX
2025-06-06 20:25:59 +08:00
committed by GitHub
parent 5d0e9fd19a
commit 9a4eb94ca9
2 changed files with 8 additions and 8 deletions
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8
vllm_ascend/worker/worker.py
View File

@@ -140,7 +140,7 @@ class NPUWorker(LocalOrDistributedWorkerBase):
experimental_config = torch_npu.profiler._ExperimentalConfig(
export_type=torch_npu.profiler.ExportType.Text,
profiler_level=torch_npu.profiler.ProfilerLevel.Level0,
profiler_level=torch_npu.profiler.ProfilerLevel.Level1,
msprof_tx=False,
aic_metrics=torch_npu.profiler.AiCMetrics.AiCoreNone,
l2_cache=False,
@@ -155,9 +155,9 @@ class NPUWorker(LocalOrDistributedWorkerBase):
torch_npu.profiler.ProfilerActivity.CPU,
torch_npu.profiler.ProfilerActivity.NPU,
],
with_stack=True,
profile_memory=True,
with_modules=True,
with_stack=False,
profile_memory=False,
with_modules=False,
experimental_config=experimental_config,
on_trace_ready=torch_npu.profiler.tensorboard_trace_handler(
torch_profiler_trace_dir))

8
vllm_ascend/worker/worker_v1.py
View File

@@ -275,7 +275,7 @@ class NPUWorker(WorkerBase):
experimental_config = torch_npu.profiler._ExperimentalConfig(
export_type=torch_npu.profiler.ExportType.Text,
profiler_level=torch_npu.profiler.ProfilerLevel.Level0,
profiler_level=torch_npu.profiler.ProfilerLevel.Level1,
msprof_tx=False,
aic_metrics=torch_npu.profiler.AiCMetrics.AiCoreNone,
l2_cache=False,
@@ -290,9 +290,9 @@ class NPUWorker(WorkerBase):
torch_npu.profiler.ProfilerActivity.CPU,
torch_npu.profiler.ProfilerActivity.NPU,
],
with_stack=True,
profile_memory=True,
with_modules=True,
with_stack=False,
profile_memory=False,
with_modules=False,
experimental_config=experimental_config,
on_trace_ready=torch_npu.profiler.tensorboard_trace_handler(
torch_profiler_trace_dir))