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check batch_size % utilized_device_count #3276

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May 21, 2021
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@glenn-jocher glenn-jocher commented May 21, 2021

Bug fix to check batch_size divisibility of utilized CUDA device count vs total system CUDA device count. Partially addresses issue #2491.

πŸ› οΈ PR Summary

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🌟 Summary

Improved CUDA device selection logic in the YOLOv5 codebase.

πŸ“Š Key Changes

  • Modified the CUDA device selection to support specifying devices via a comma-separated string.
  • Ensured the batch size is divisible by the number of selected GPUs, rather than the total available GPUs.
  • Updated the display of GPU properties to reflect the new device selection method.

🎯 Purpose & Impact

  • Allows users more flexibility in choosing specific GPUs for training, especially on systems with multiple GPUs. πŸ—οΈ
  • Guarantees the batch size is appropriately set for the number of GPUs in use, which can enhance performance. πŸš€
  • Enhances clarity for users when multiple GPUs are selected by displaying the respective device properties. πŸ–₯️

Bug fix to check batch_size divisibility of utilized CUDA device count vs total system CUDA device count.
@glenn-jocher glenn-jocher merged commit f340235 into master May 21, 2021
@glenn-jocher glenn-jocher deleted the glenn-jocher-patch-1 branch May 21, 2021 13:20
Lechtr pushed a commit to Lechtr/yolov5 that referenced this pull request Jul 20, 2021
Bug fix to check batch_size divisibility of utilized CUDA device count vs total system CUDA device count.

(cherry picked from commit f340235)
BjarneKuehl pushed a commit to fhkiel-mlaip/yolov5 that referenced this pull request Aug 26, 2022
Bug fix to check batch_size divisibility of utilized CUDA device count vs total system CUDA device count.
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