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In this tutorial, we will guide you through the process of installing PyTorch with GPU support on Ubuntu using Conda. Conda is a powerful package management and environment management system that simplifies the installation and management of software packages.
Before you begin, ensure that you have the following prerequisites:
If you haven't installed Conda on your system, you can follow the official documentation for Conda installation: Installing Conda
Open a terminal and create a new Conda environment using the following command:
Replace "myenv" with your preferred environment name.
Activate the Conda environment:
Now that you have activated your Conda environment, you can install PyTorch with GPU support. Run the following command:
Replace version with the version of CUDA toolkit installed on your system (e.g., cudatoolkit=11.1).
For example:
You can verify the installation by running a simple Python script within your Conda environment:
Save the script to a file (e.g., verify_pytorch_installation.py) and run it using:
If everything is set up correctly, you should see output indicating that CUDA is available and the version of CUDA being used.
Congratulations! You have successfully installed PyTorch with GPU support using Conda on Ubuntu. You can now start developing and running PyTorch applications that leverage the power of your GPU for accelerated computations.
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