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[Chore] Separate out profiling utilities from vllm.utils (#27150)

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Signed-off-by: dongbo910220 <1275604947@qq.com>
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dongbo910220
2025-10-19 03:12:01 +08:00
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parent 9f020f4f31
commit a1946c9f61
3 changed files with 89 additions and 50 deletions
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14
docs/contributing/profiling.md
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@ -180,9 +180,13 @@ The profiling traces generated by the continuous profiling workflow are publicly
The Python standard library includes
[cProfile](https://docs.python.org/3/library/profile.html) for profiling Python
code. vLLM includes a couple of helpers that make it easy to apply it to a section of vLLM.
Both the `vllm.utils.cprofile` and `vllm.utils.cprofile_context` functions can be
Both the `vllm.utils.profiling.cprofile` and `vllm.utils.profiling.cprofile_context` functions can be
used to profile a section of code.
!!! note
The legacy import paths `vllm.utils.cprofile` and `vllm.utils.cprofile_context` are deprecated.
Please use `vllm.utils.profiling.cprofile` and `vllm.utils.profiling.cprofile_context` instead.
### Example usage - decorator
The first helper is a Python decorator that can be used to profile a function.
@ -190,9 +194,9 @@ If a filename is specified, the profile will be saved to that file. If no filena
specified, profile data will be printed to stdout.
```python
import vllm.utils
from vllm.utils.profiling import cprofile
@vllm.utils.cprofile("expensive_function.prof")
@cprofile("expensive_function.prof")
def expensive_function():
# some expensive code
pass
@ -204,13 +208,13 @@ The second helper is a context manager that can be used to profile a block of
code. Similar to the decorator, the filename is optional.
```python
import vllm.utils
from vllm.utils.profiling import cprofile_context
def another_function():
# more expensive code
pass
with vllm.utils.cprofile_context("another_function.prof"):
with cprofile_context("another_function.prof"):
another_function()
```