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This PR adds functionality to automatically select GPUs with the most available memory when the number of training devices specified by the user is less than the total GPUs available. In this case, we query the memory utilization of each GPU, sort them by free memory, and allocate the devices with the highest availability.

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codecov bot commented Sep 18, 2025

Codecov Report

❌ Patch coverage is 86.66667% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 93.49%. Comparing base (ff91433) to head (5a87d7c).
⚠️ Report is 39 commits behind head on main.

Files with missing lines Patch % Lines
sleap_nn/training/utils.py 83.33% 4 Missing ⚠️

❌ Your patch status has failed because the patch coverage (86.66%) is below the target coverage (95.00%). You can increase the patch coverage or adjust the target coverage.

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #333      +/-   ##
==========================================
- Coverage   95.28%   93.49%   -1.80%     
==========================================
  Files          49       49              
  Lines        6765     6962     +197     
==========================================
+ Hits         6446     6509      +63     
- Misses        319      453     +134     

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@gitttt-1234 gitttt-1234 merged commit 6e11050 into main Sep 19, 2025
11 of 13 checks passed
@gitttt-1234 gitttt-1234 deleted the divya/auto-select-gpu branch September 19, 2025 03:27
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2 participants