-
-
Notifications
You must be signed in to change notification settings - Fork 16.2k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
about physical memory and virtual memory #13058
Comments
@Songpenglei123 hello! Thank you for reaching out with your question. 🌟 During training, YOLOv5 utilizes virtual memory to handle large datasets that might not fit entirely into physical RAM. This approach allows the system to swap parts of the data between physical memory and disk space (virtual memory), enabling the processing of larger datasets without running out of physical memory. The usage of virtual memory as you described seems to be a part of this mechanism, especially when dealing with extensive data or high-resolution images. If you find that the virtual memory usage is excessively high, you might consider:
These adjustments can help manage memory usage more effectively during training. If you have further questions or need more specific advice, feel free to ask! |
👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help. For additional resources and information, please see the links below:
Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed! Thank you for your contributions to YOLO 🚀 and Vision AI ⭐ |
Search before asking
Question
Why are all the images loaded into the virtual memory during training? I set the virtual memory to about 300g and the physical memory to 128g
Additional
No response
The text was updated successfully, but these errors were encountered: