The ray tune result is incomplete about ultralytics HOT 3 OPEN

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Install

Pip install the ultralytics package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.

pip install ultralytics

Environments

YOLOv8 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

• Notebooks with free GPU:
• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Amazon Deep Learning AMI. See AWS Quickstart Guide
• Docker Image. See Docker Quickstart Guide

Status

If this badge is green, all Ultralytics CI tests are currently passing. CI tests verify correct operation of all YOLOv8 Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.

from ultralytics.

@Eastar-star hi there,

Thank you for reaching out and providing detailed information about the issue you're encountering with Ray Tune and YOLOv8. Let's work through this together to identify the root cause and find a solution.

Firstly, could you please confirm that you are using the latest versions of both torch and ultralytics? Ensuring that you have the most recent versions can often resolve unexpected issues. You can update your packages using the following commands:

pip install --upgrade torch ultralytics

Next, it's crucial to have a minimum reproducible example to help us diagnose the problem effectively. If you haven't already, please provide a snippet of your code that reproduces the issue. This will enable us to investigate further. You can find more information on creating a minimum reproducible example here: Minimum Reproducible Example.

Regarding the missing files in the tune directory, it seems like the expected outputs (best_hyperparameters.yaml, best_fitness.png, tune_results.csv, tune_scatter_plots.png, and the weights) are not being generated. This could be due to several reasons, such as the configuration of the tuning process or the specific settings used.

Here are a few steps you can take to troubleshoot and potentially resolve the issue:

1. Check the Ray Tune Logs: Ensure that there are no errors or warnings in the Ray Tune logs that might indicate why these files are not being generated.

2. Verify the Configuration: Ensure that your tune() method is correctly configured. For example, make sure that the epochs parameter is set appropriately and that the space dictionary is correctly defined.

3. Inspect the Results: After running the tuning process, you can inspect the results programmatically to ensure that the tuning process completed successfully. Here’s an example of how you can do this:

   from ultralytics import YOLO
   
   # Load a YOLOv8n model
   model = YOLO("yolov8n.pt")
   
   # Start tuning hyperparameters for YOLOv8n training on the COCO8 dataset
   result_grid = model.tune(data="coco128.yaml", use_ray=True)
   
   # Check the results
   if result_grid.errors:
       print("One or more trials failed!")
   else:
       print("No errors!")
   
   for i, result in enumerate(result_grid):
       print(f"Trial #{i}: Configuration: {result.config}, Last Reported Metrics: {result.metrics}")

4. Manual Inspection: Manually inspect the runs/detect/tune directory to see if any files are being generated and if they contain the expected data.

If the issue persists after these steps, please provide the additional details requested, and we will continue to assist you in resolving this matter.

Thank you for your patience and cooperation. We look forward to helping you get this resolved! 😊

from ultralytics.

👋 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:

• Docs: https://docs.ultralytics.com
• HUB: https://hub.ultralytics.com
• Community: https://community.ultralytics.com

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 ⭐

from ultralytics.