PyTorch can be installed and used on various Windows distributions. Here we will construct a randomly initialized tensor. To ensure that PyTorch was installed correctly, we can verify the installation by running sample PyTorch code. Then, run the command that is presented to you. To install PyTorch via pip, and do have a ROCm-capable system, in the above selector, choose OS: Linux, Package: Pip, Language: Python and the ROCm version supported. Often, the latest CUDA version is better. To install PyTorch via pip, and do have a CUDA-capable system, in the above selector, choose OS: Linux, Package: Pip, Language: Python and the CUDA version suited to your machine. GPU support), in the above selector, choose OS: Linux, Package: Pip, Language: Python and Compute Platform: CPU. To install PyTorch via pip, and do not have a CUDA-capable or ROCm-capable system or do not require CUDA/ROCm (i.e. PyTorch via Anaconda is not supported on ROCm currently. To install PyTorch via Anaconda, and you do have a CUDA-capable system, in the above selector, choose OS: Linux, Package: Conda and the CUDA version suited to your machine. GPU support), in the above selector, choose OS: Linux, Package: Conda, Language: Python and Compute Platform: CPU. To install PyTorch via Anaconda, and do not have a CUDA-capable or ROCm-capable system or do not require CUDA/ROCm (i.e. Tip: If you want to use just the command pip, instead of pip3, you can symlink pip to the pip3 binary. If you decide to use APT, you can run the following command to install it: However, if you want to install another version, there are multiple ways: If you want to use just the command python, instead of python3, you can symlink python to the python3 binary. Tip: By default, you will have to use the command python3 to run Python. Python 3.8-3.11 is generally installed by default on any of our supported Linux distributions, which meets our recommendation. The specific examples shown were run on an Ubuntu 18.04 machine. An example difference is that your distribution may support yum instead of apt. The install instructions here will generally apply to all supported Linux distributions. PyTorch is supported on Linux distributions that use glibc >= v2.17, which include the following: Prerequisites Supported Linux Distributions It is recommended, but not required, that your Linux system has an NVIDIA or AMD GPU in order to harness the full power of PyTorch’s CUDA support or ROCm support. Depending on your system and compute requirements, your experience with PyTorch on Linux may vary in terms of processing time. PyTorch can be installed and used on various Linux distributions. If you use the command-line installer, you can right-click on the installer link, select Copy Link Address, or use the following commands on Intel Mac: To install Anaconda, you can download graphical installer or use the command-line installer. Anaconda is the recommended package manager as it will provide you all of the PyTorch dependencies in one, sandboxed install, including Python. To install the PyTorch binaries, you will need to use one of two supported package managers: Anaconda or pip. In one of the upcoming PyTorch releases, support for Python 3.8 will be deprecated. Package manager (see below), Homebrew, or You can install Python either through the Anaconda It is recommended that you use Python 3.8 - 3.11. PyTorch is supported on macOS 10.15 (Catalina) or above. Depending on your system and GPU capabilities, your experience with PyTorch on a Mac may vary in terms of processing time. PyTorch can be installed and used on macOS.
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