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Sure thing! Installing PyTorch on Linux is a straightforward process, and I’ll guide you through the steps using a code example. Let’s assume you want to install PyTorch with GPU support (CUDA) for better performance. Follow these steps:
Conda is a package manager that helps manage dependencies for Python packages. You can download and install Miniconda, a minimal version of Anaconda, by visiting Miniconda’s website. Follow the installation instructions for your Linux distribution.
Open a terminal and create a new Conda environment for PyTorch. You can replace myenv with your preferred environment name.
Activate the environment:
Now, let’s install PyTorch. Visit the official PyTorch website to get the installation command. As of my last knowledge update in January 2022, the command for CUDA-enabled PyTorch is:
Replace cudatoolkit=10.2 with your CUDA toolkit version if it’s different.
After the installation is complete, verify that PyTorch is installed correctly by opening a Python interpreter within your Conda environment:
Then, in the Python interpreter, run the following:
If PyTorch is installed successfully, you should see the PyTorch version and True for CUDA availability if you have a compatible GPU.
That’s it! You’ve successfully installed PyTorch on Linux with GPU support. Remember to activate your Conda environment (conda activate myenv) whenever you want to use PyTorch.
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