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reimplementation of gpu_count #3718

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Merged
merged 3 commits into from
Mar 19, 2025

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mauriliogenovese
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fix #3717

I tried to write a simpler implementation of getGPUs from gputil package.
I used a separate file to include their license.

This need to be tested under windows with Python 3.12+ and I don't have such system, so it's untested for now.

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codecov bot commented Mar 4, 2025

Codecov Report

Attention: Patch coverage is 62.50000% with 6 lines in your changes missing coverage. Please review.

Project coverage is 73.05%. Comparing base (fe20d45) to head (c189912).
Report is 11 commits behind head on master.

Files with missing lines Patch % Lines
nipype/utils/gpu_count.py 60.00% 6 Missing ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##           master    #3718      +/-   ##
==========================================
- Coverage   73.07%   73.05%   -0.03%     
==========================================
  Files        1278     1279       +1     
  Lines       59406    59414       +8     
==========================================
- Hits        43411    43404       -7     
- Misses      15995    16010      +15     

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@mauriliogenovese mauriliogenovese force-pushed the FIX-gputil-error-on-window branch from 154f3c7 to 4dfbbbe Compare March 4, 2025 17:56
@effigies
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effigies commented Mar 5, 2025

We need to remove gputil from the dependencies.

I'm not terribly worried about Windows, as there are many years of development since last time anybody tried to get nipype working on Windows.

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mauriliogenovese commented Mar 5, 2025

We need to remove gputil from the dependencies.

Done

I'm not terribly worried about Windows, as there are many years of development since last time anybody tried to get nipype working on Windows.

I meant that I don't have a computer without a nvidia GPU to test if this code fix the error reported, I assumed it was on Windows. So even a test on other OS may be useful.

Comment on lines 28 to 55
from subprocess import Popen, PIPE
import os


def gpu_count():
try:
if platform.system() == "Windows":
nvidia_smi = shutil.which('nvidia-smi')
if nvidia_smi is None:
nvidia_smi = (
"%s\\Program Files\\NVIDIA Corporation\\NVSMI\\nvidia-smi.exe"
% os.environ['systemdrive']
)
else:
nvidia_smi = "nvidia-smi"

p = Popen(
[nvidia_smi, "--query-gpu=name", "--format=csv,noheader,nounits"],
stdout=PIPE,
)
stdout, stderror = p.communicate()

output = stdout.decode('UTF-8')
lines = output.split(os.linesep)
num_devices = len(lines) - 1
return num_devices
except:
return 0
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If the goal is to keep it as close to the source as possible, that's fine. Here are some cleanups for your consideration:

  1. Use shutil.which() unconditionally. We can detect a FileNotFoundError before calling the process and simply return 0.
  2. Use subprocess.run, which is the recommended API. By using text mode, we don't have to handle decoding or newline normalization.
  3. Use targeted errors. FileNotFoundError and PermissionError (both OSErrors) should catch failures to run. UnicodeDecodeError will catch bad output.
  4. Use p.output.splitlines() to get content-full lines. A trailing newline does not produce an empty string at the end of the list.
Suggested change
from subprocess import Popen, PIPE
import os
def gpu_count():
try:
if platform.system() == "Windows":
nvidia_smi = shutil.which('nvidia-smi')
if nvidia_smi is None:
nvidia_smi = (
"%s\\Program Files\\NVIDIA Corporation\\NVSMI\\nvidia-smi.exe"
% os.environ['systemdrive']
)
else:
nvidia_smi = "nvidia-smi"
p = Popen(
[nvidia_smi, "--query-gpu=name", "--format=csv,noheader,nounits"],
stdout=PIPE,
)
stdout, stderror = p.communicate()
output = stdout.decode('UTF-8')
lines = output.split(os.linesep)
num_devices = len(lines) - 1
return num_devices
except:
return 0
import subprocess
import os
def gpu_count():
nvidia_smi = shutil.which('nvidia-smi')
if nvidia_smi is None and platform.system() == "Windows":
nvidia_smi = f'{os.environ["systemdrive"]}\\Program Files\\NVIDIA Corporation\\NVSMI\\nvidia-smi.exe'
if nvidia_smi is None:
return 0
try:
p = subprocess.run(
[nvidia_smi, "--query-gpu=name", "--format=csv,noheader,nounits"],
stdout=subprocess.PIPE,
text=True,
)
except (OSError, UnicodeDecodeError):
return 0
return len(output.splitlines())

@effigies effigies merged commit 8732bf6 into nipy:master Mar 19, 2025
25 checks passed
effigies added a commit that referenced this pull request Mar 19, 2025
1.10.0 (March 19, 2025)

New feature release in the 1.10.x series.

This release adds GPUs to multiprocess resource management.
In general, no changes to existing code should be required if the GPU-enabled
interface has a ``use_gpu`` input.
The ``n_gpu_procs`` can be used to set the number of GPU processes that may
be run in parallel, which will override the default of GPUs identified by
``nvidia-smi``, or 1 if no GPUs are detected.

* FIX: Reimplement ``gpu_count()`` (#3718)
* FIX: Avoid 0D array in ``algorithms.misc.merge_rois`` (#3713)
* FIX: Allow nipype.sphinx.ext.apidoc Config to work with Sphinx 8.2.1+ (#3716)
* FIX: Resolve crashes when running workflows with updatehash=True (#3709)
* ENH: Support for gpu queue (#3642)
* ENH: Update to .wci.yml (#3708)
* ENH: Add Workflow Community Initiative (WCI) descriptor (#3608)
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[ENH] Multiproc always looks for GPUs making it impossible to run pipelines on CPU-only machines
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