How to Install PyTorch for Windows with GPU Support

PyTorch is an open-source machine learning library developed by Facebook’s AI Research lab. It is known for its ease of use and flexibility, making it a popular choice for researchers and developers working on deep learning projects. In this article, we will walk you through the steps to install PyTorch for Windows with GPU support.

Step 1: Check your GPU compatibility

Before you begin the installation process, it is important to ensure that your GPU is compatible with PyTorch. You can check the list of supported CUDA-enabled GPUs on NVIDIA’s website to verify compatibility.

Step 2: Install CUDA

PyTorch requires CUDA, a parallel computing platform and application programming interface (API) model created by NVIDIA, to run on GPUs. You can download the latest version of CUDA from NVIDIA’s official website and follow the installation instructions provided.

Step 3: Install cuDNN

cuDNN (CUDA Deep Neural Network library) is a GPU-accelerated library of primitives for deep neural networks developed by NVIDIA. It is a crucial component for running deep learning frameworks like PyTorch on GPUs. You can download cuDNN from the NVIDIA Developer website and install it following the provided instructions.

Step 4: Install PyTorch

Once you have CUDA and cuDNN installed, you can proceed to install PyTorch with GPU support. You can use the following pip command to install the latest stable release of PyTorch for Windows with GPU support:

pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio===0.9.0 -f https://download.pytorch.org/whl/torch_stable.html

This command will install the necessary packages for PyTorch to run on your Windows machine with GPU support.

Step 5: Verify the installation

After the installation is complete, you can verify that PyTorch is running with GPU support by running a simple Python script that utilizes the GPU. If everything was installed correctly, you should see the script executing on the GPU instead of the CPU.

Conclusion

By following the steps outlined in this article, you can easily install PyTorch for Windows with GPU support and start leveraging the power of your GPU for deep learning tasks. It is important to carefully follow the installation instructions for CUDA and cuDNN to ensure a smooth installation process for PyTorch with GPU support.