Modulenotfounderror: no module named ‘torch_sparse’ [SOLVED]

What is an error stating modulenotfounderror: no module named ‘torch_sparse’?

Are you working on an object detection project and are bothered by the sudden pop-up of this error?

It’s time to chill, as in this article we will teach you how to solve this problem.

Before we dive into our tutorial, let’s first know when this error occurs.

This error occurs when the essential ‘torch_sparse’ module is not found in your system or Python environment.

What is Python?

Python is one of the most popular programming languages.

It is used for developing a wide range of applications.

In addition, Python is a high-level programming language that is used by most developers due to its flexibility.

What is torch_sparse?

Torch_sparse is a third-party PyTorch module that offers sparse tensor operations.

The package Pytorch Sparse contains a modest extension library of optimized sparse matrix operations with support for autograd.

Now, let’s move on to our tutorial.

How to solve “no module named ‘torch_sparse’” in Python

The following are the steps on how to resolve the error “modulenotfounderror: no module named ‘torch_sparse’” in Python.

  1. Check if the ‘torch_sparse’ module is installed.

    The first step is to check if the torch_sparse module is installed in your Python environment or system.

    To check, open the cmd or command prompt, then type the command pip list.

    pip list

    The command pip list will show you the list of installed modules on your system.

    Moving on, if the torch_sparse module is not found, move to the next step.

    However, if the torch_sparse module is already installed, skip the next steps and proceed to the tip below.

  2. Install the ‘torch_sparse’ module.

    If the torch_sparse module is not found in your Python environment or system, install it.

    To install, input the command pip install torch_sparse.

    pip install torch_sparse

    The command pip install torch_sparse will download and install the latest version of the torch_sparse module on your system.

  3. Import.

    You can now import torch_sparse if the installation is successful in your code.

    To do so, input:

    import torch_sparse

Tip: If you’ve already installed a torch_sparse module in your system and you encounter this error, try to upgrade it.

  • To upgrade the torch_sparse module, input the following command:

    pip install –upgrade torch_sparse

    The command pip install –upgrade torch_sparse will upgrade the torch_sparse module to its latest version.

    If your torch_sparse module is already the latest version, this will come out: “Requirement already satisfied.”

Note: If you get an error message stating that “pip” cannot be found, use the command python -m.

It will look like this: python -m pip install torch_sparse.

There’s also a possibility that your pip is outdated, and you have to upgrade it.

To do so, enter the following command:

pip install --upgrade pip

The command pip install –upgrade pip will upgrade the pip package manager to its newest version.

However, if your pip is already in the latest version, this will come out: “Requirement already satisfied.”

Another way of solving the error “no module named ‘torch_sparse’”

If you’re not using the correct version of Python, there are instances where it still has this error even though you have installed the torch_sparse module.

So, what you’ll do is:

  • Check out the Python version.

    Confirm that you’re using the right Python version that has the torch_sparse module installed if you have numerous versions of Python installed on your system.

    To do so, you can check your Python version by inputting python –version into your command prompt.

    python version

    The command python –version will display the version of Python installed on your system.


In conclusion, the error modulenotfounderror: no module named ‘torch_sparse’ can be easily solved by:

“Checking if the torch_sparse module is installed in your Python environment and, if not, by installing it.”

By following the guide above, there’s no doubt that you’ll be able to resolve this error quickly.

That is all for this article, IT source coders!

We hope you’ve learned something from this.

Thank you for reading!

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