PyTorch Installation with CUDA

In this article, we will guide you through the installation process of PyTorch with CUDA. CUDA is a parallel computing platform and application programming interface model created by Nvidia for general-purpose computing on their GPUs. PyTorch is an open-source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.

Virtual Environment Creation

It is recommended to create a virtual environment using virtualenv before installing PyTorch with CUDA. This helps in managing dependencies and isolating the project from other Python installations. Here is how you can create a virtual environment:

        
            $ pip install virtualenv
            $ virtualenv myenv
            $ source myenv/bin/activate
        
    

PyTorch Installation

Now that you have created a virtual environment, you can proceed with installing PyTorch with CUDA. Here is how you can install PyTorch using pip:

        
            $ pip install torch torchvision
        
    

If you want to install PyTorch with CUDA support, you can specify the CUDA version while installing:

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

Jupyter Notebook Installation

Jupyter Notebook is a popular tool for interactive data science and machine learning. Here is how you can install Jupyter Notebook within your virtual environment:

        
            $ pip install jupyter
            $ jupyter notebook