Importerror: cannot import name get_num_classes from torchmetrics.utilities.data

Have you encountered the “ImportError: cannot import name get_num_classes from torchmetrics.utilities.data” error while working with PyTorch and Torchmetrics?

Honestly, this error is caused when the Python interpreter fails to locate the “get_num_classes” function in the Torchmetrics library.

It is a common error that can be frustrating and time-consuming to resolve, but it is crucial to fix it to ensure that your PyTorch models are functioning correctly.

But before fixing this error, let’s understand the key terms first.

What is Torchmetrics?

Torchmetrics is a PyTorch library that provides a wide range of metrics for evaluating and improving the performance of deep learning models.

Additionally, this is designed to be compatible with PyTorch and provides a simple and intuitive API for working with different metrics, including accuracy, precision, recall, F1 score, and many others.

Further, Torchmetrics is an essential tool for deep learning practitioners as it helps to identify performance issues and provides insights into the behavior of the models.

All in all, it is a lightweight library that can be easily integrated into any PyTorch project, making it a popular choice among researchers and developers.

Understanding the “get_num_classes” function

The “get_num_classes” function is a utility function provided by Torchmetrics that returns the number of classes in a multi-class classification problem.

It is commonly used in deep learning projects that involve classification tasks, such as image classification, sentiment analysis, and natural language processing.

Moreover, “get_num_classes” function takes a dataset or a dataloader as input and returns the number of classes in the dataset.

Eventually, it is a handy function that saves time and effort in calculating the number of classes manually.

Now that you understand the key terms involved, let’s jump on to understanding the error.

What is cannot import name get_num_classes from torchmetrics.utilities.data?

The “ImportError: cannot import name get_num_classes from torchmetrics.utilities.data” error occurs when you are trying to import the get_num_classes function from the data module within the torchmetrics.utilities package, but the function cannot be found.

Causes of the “ImportError” in Torchmetrics

Here are the possible causes of “ImportError: cannot import name get_num_classes from torchmetrics.utilities.data” error:

  • Outdated version of Torchmetrics
  • Missing dependencies
  • Using an incorrect import statement
  • Problems with your Python environment

Fixing the “ImportError” in Torchmetrics

To fix the “ImportError” in Torchmetrics, you need to update the library and install any missing dependencies.

Here’s how you can do it:

Updating Torchmetrics

To update Torchmetrics, you can use the following command in your terminal:

pip install torchmetrics --upgrade

This command will update your Torchmetrics library to the latest version, ensuring that the “get_num_classes” function is available in your library.

Installing missing dependencies

Another way is to install missing dependencies, you can use the following command in your terminal:

pip install [dependency-name]

Replace “[dependency-name]” with the name of the missing dependency. You can find the name of the dependency in the error message that you receive.

Once you have installed all the missing dependencies, the “get_num_classes” function should work correctly.

Use the correct import statement

Additionally, ensure that you are using the correct import statement for the get_num_classes function.

It should be like this:

from torchmetrics.utilities.data import get_num_classes

Restart your Python environment

Sometimes, restarting your Python environment (e.g., closing and reopening your IDE or command prompt) can resolve import errors.

Anyway, here are other fixed errors you can consider when somehow you might encounter them.

Conclusion

In conclusion, the “ImportError: cannot import name get_num_classes from torchmetrics.utilities.data” error is a common issue that occurs when the Python interpreter fails to locate the “get_num_classes” function in the Torchmetrics library. It can be resolved by updating the library and installing any missing dependencies.

I hope this article has helped you fix the error.

Until next time! 😊

Frequently Asked Questions

What is Python ImportError and what causes it?

ImportError is raised when an import fails for any reason. The most specific subtype is ModuleNotFoundError (no such module). Plain ImportError typically means the module exists but a name inside it can’t be imported, e.g. ‘cannot import name X from Y’ (X was renamed, removed, or moved between versions of Y). Common with library version mismatches.

How do I fix ‘cannot import name X from Y’?

Three steps: (1) Check the library version: pip show Y. (2) Check the changelog of Y, X may have been renamed or removed in a recent release. (3) Either pin to an older Y version (pip install Y==1.x.y) or update your code to the new import path. Common 2025-2026 examples: Werkzeug url_decode removed, Pillow ANTIALIAS renamed to LANCZOS.

Why does the import work in REPL but fail in script?

Two reasons. (1) Different Python interpreter: REPL uses one Python, your script uses another. Run python –version both times. (2) Different working directory: REPL is started where you have access to local modules, script is run from a different cwd. Add the project path to sys.path or use python -m to run as a module.

How do I avoid circular import errors?

Circular imports happen when module A imports B and B imports A at the top level. Three fixes: (1) Move one import inside the function that uses it (lazy import). (2) Restructure code so A and B both import from a third module C. (3) Use TYPE_CHECKING for type-hint-only imports: if TYPE_CHECKING: from a import X.

Where can I find more ImportError fixes?

Browse the ImportError reference hub for 67+ specific fixes (Flask, Werkzeug, Django, ML library versions). For missing-module cases see ModuleNotFoundError. For Python setup help see Python Tutorial hub.