[Fix]AttributeError: ‘AdamWarmup’ object has no attribute ‘_set_hyper’

The error message you’re encountering, AttributeError: 'AdamWarmup' object has no attribute '_set_hyper', suggests that there is an issue with the implementation of the AdamWarmup optimizer. It seems like the optimizer is missing a method or attribute called _set_hyper, which is expected to be present according to the code or library you’re using.

To resolve this issue, you can try the following steps:

1. Update Library/Package: Make sure you’re using the latest version of the library or package that includes the AdamWarmup optimizer. Sometimes, such issues are resolved in newer versions with bug fixes or feature enhancements.
2. Check Implementation: If you’re implementing the AdamWarmup optimizer yourself or using a custom implementation, double-check the code to ensure that the _set_hyper method or attribute is correctly defined. It’s possible that there’s a typo or a missing implementation causing the error.
3. Library Documentation: Refer to the documentation or source code of the library or package you’re using to see if there are any specific requirements or changes needed to use the AdamWarmup optimizer correctly. It’s possible that there are additional steps or configurations required that you might have missed.
4. Community Forums: Look for discussions or forums related to the library or package you’re using. Others might have encountered similar issues and found solutions or workarounds that could help you resolve the problem.
5. Alternative Optimizers: If you’re unable to resolve the issue with the AdamWarmup optimizer, consider using an alternative optimizer that is available and well-supported. There are many optimizer options available in popular deep learning frameworks like TensorFlow and PyTorch.

By following these steps and troubleshooting the issue systematically, you should be able to resolve the AttributeError and continue with your implementation successfully.