How to Fix AssertionError: torch not compiled with cuda enabled

The AssertionError: torch not compiled with cuda enabled error occurs when you use PyTorch library that has not been compiled with support for CUDA, a parallel computing platform and API for GPUs.

To fix the AssertionError: torch not compiled with cuda enabled error, install the necessary libraries using this command: conda install -c pytorch torchvision cudatoolkit=10.1 pytorch.

import torch

print(torch.__version__)
my_tensor = torch.tensor([[1, 2, 3], [4, 5, 6]], dtype=torch.float32, device="cpu")
print(my_tensor)
torch.cuda.is_available()

We first imported the PyTorch library in the above code example and then printed its version.

Then, we created a tensor with two rows and three columns using the torch.tensor() method.

The data type of the tensor is set to torch.float32, and the device is set to “cpu”.

Finally, we call the torch.cuda.is_available() method to check if CUDA is available on the system.

The output of the print(torch.__version__) statement will be a string indicating the version of PyTorch that is installed.

Printed the output representing the created tensor with the values and data type information.

The output of torch.cuda.is_available() method will be a boolean value indicating whether CUDA is available on the system (True if it is available, False otherwise).

Output

We verified the installation of CUDA by using the torch.cuda.is_available() function is not installed on my machine because it returns False.

The alternate solution for this problem is to use the following command.

pip install torch===1.5.0 torchvision===0.6.0 -f https://download.pytorch.org/whl/torch_stable.html

If the issue persists, then you can try installing the following command.

conda install cudatoolkit

In some cases, you need to install the “cpuonly” package, which needs to be removed.

Make sure that CUDA and PyTorch are installed in the correct environment, or try reinstalling both with the correct versions.

There are numerous situations in which you might encounter this issue. Sometimes CUDA support is obvious.

PyTorch with CUDA is a version of the PyTorch library that has been compiled with support for the NVIDIA CUDA platform, which provides hardware acceleration for computationally intensive tasks such as machine learning and data processing.

However, in some cases, it indirectly calls CUDA, which is expressly concealed.

I hope these solutions will resolve the issues you are having.