python pytorch cuda install

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PyTorch is a popular deep learning library in Python, and CUDA is a parallel computing platform and programming model developed by NVIDIA. CUDA support in PyTorch allows you to leverage the power of NVIDIA GPUs for faster computation. This tutorial will guide you through the process of installing PyTorch with CUDA support.
Before installing PyTorch with CUDA support, you need to install the NVIDIA CUDA Toolkit. Visit the official NVIDIA CUDA Toolkit download page: https://developer.nvidia.com/cuda-dow...
Select your operating system and follow the instructions to install the CUDA Toolkit.
cuDNN is a GPU-accelerated library for deep neural networks. Download cuDNN from the NVIDIA cuDNN download page: https://developer.nvidia.com/cudnn
Follow the provided instructions to install cuDNN on your system.
Now that you have CUDA and cuDNN installed, you can proceed to install PyTorch with CUDA support using pip.
Replace version with the desired version number. You can find the latest version on the PyTorch website.
Once the installation is complete, you can verify that PyTorch is using CUDA by running the following Python code:
This code snippet checks if CUDA is available, prints the CUDA version, the number of available GPUs, and the name of each GPU.
That's it! You have successfully installed PyTorch with CUDA support on your system. Now you can accelerate your deep learning computations using the power of NVIDIA GPUs.
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