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description: Discover how to automatically estimate the best YOLO batch size for optimal CUDA memory usage in PyTorch using Ultralytics' autobatch utility. |
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keywords: YOLO batch size, CUDA memory, PyTorch autobatch, Ultralytics, machine learning, optimal batch size, training batch size, YOLO model |
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# Reference for `ultralytics/utils/autobatch.py` |
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!!! Note |
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This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/autobatch.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/autobatch.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/utils/autobatch.py) 🛠️. Thank you 🙏! |
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<br> |
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## ::: ultralytics.utils.autobatch.check_train_batch_size |
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<br><br><hr><br> |
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## ::: ultralytics.utils.autobatch.autobatch |
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<br><br>
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