Update train.py

[ShubhamPhapale]

updated deprecated call

🛠️ PR Summary

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🌟 Summary

Updated AMP (Automatic Mixed Precision) autocast usage for compatibility with PyTorch 2.0+.

📊 Key Changes

• Replaced torch.cuda.amp.autocast(amp) with torch.amp.autocast('cuda', amp) in the training script.

🎯 Purpose & Impact

• Purpose: Aligns the code with PyTorch 2.0+ updates, making YOLOv5 compatible with newer PyTorch versions.
• Impact: Prevents potential errors or deprecation warnings, ensuring smoother training experiences for users upgrading to the latest PyTorch versions. 🚀

[github-actions[bot]]

All Contributors have signed the CLA. ✅
_{Posted by the CLA Assistant Lite bot.}

[UltralyticsAssistant]

👋 Hello @ShubhamPhapale, thank you for submitting a ultralytics/yolov5 🚀 PR! To ensure a seamless integration of your work, please review the following checklist:

• ✅ Define a Purpose: Clearly explain the purpose of your fix or feature in your PR description, and link to any relevant issues. Ensure your commit messages are clear, concise, and adhere to the project's conventions.
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• ✅ Update Documentation: Update the relevant documentation for any new or modified features.
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🛠️ Notes

It looks like your PR updates AMP autocast usage for compatibility with PyTorch 2.0+, which is an important improvement.

If applicable, please include a minimum reproducible example (MRE) so we can fully understand and test the impact of this change. For example, providing specific training scenarios where the prior implementation failed due to autograd issues with PyTorch 2.0+ would help validate this fix.

An Ultralytics engineer will also review this PR shortly. Stay tuned for additional feedback! 🚀

_{Made with ❤️ by Ultralytics Actions}

[ShubhamPhapale]

I have read the CLA Document and I sign the CLA

[github-actions[bot]]

👋 Hello there! We wanted to let you know that we've decided to close this pull request due to inactivity. We appreciate the effort you put into contributing to our project, but unfortunately, not all contributions are suitable or aligned with our product roadmap.

We hope you understand our decision, and please don't let it discourage you from contributing to open source projects in the future. We value all of our community members and their contributions, and we encourage you to keep exploring new projects and ways to get involved.

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