Скачать или смотреть python install pytorch with cuda windows

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Certainly! Installing PyTorch with CUDA support on Windows involves several steps. Here is a step-by-step tutorial with code examples:
Before installing PyTorch with CUDA, ensure that your GPU is CUDA-compatible. You can check the CUDA compatibility of your GPU on the official NVIDIA website.
Download and install the CUDA Toolkit: Visit the NVIDIA CUDA Toolkit download page and download the appropriate version for your GPU.
Download and install cuDNN: Visit the NVIDIA cuDNN download page and download the cuDNN version compatible with your CUDA Toolkit. Follow the installation instructions provided.
Installing Anaconda is optional but recommended as it simplifies package management and environment setup. You can download Anaconda from the official website.
Open a terminal and create a virtual environment using the following commands:
Replace "myenv" with your desired environment name.
Run the following commands to install PyTorch with CUDA support:
This command installs PyTorch, torchvision, and torchaudio with CUDA support for CUDA Toolkit 11.1. Adjust the cudatoolkit version according to your installed version.
To verify the installation, launch Python in your terminal and run the following code:
If everything is set up correctly, you should see information about your GPU.
You have successfully installed PyTorch with CUDA support on Windows. Make sure to check the official PyTorch documentation for any updates or additional information: PyTorch Installation Guide.
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