From 974674e2a6d89a2c0ef7e019d654e14858093bb7 Mon Sep 17 00:00:00 2001 From: Svetlana Karslioglu Date: Tue, 23 Apr 2024 11:49:04 -0700 Subject: [PATCH 1/2] Small fix into quickstart module --- _includes/quick_start_local.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_includes/quick_start_local.html b/_includes/quick_start_local.html index d6273cfe5edc..59ea52366dbb 100644 --- a/_includes/quick_start_local.html +++ b/_includes/quick_start_local.html @@ -5,7 +5,7 @@ install previous versions of PyTorch. Note that LibTorch is only available for C++.

-

NOTE: Latest PyTorch requires Python 3.8 or later. For more details, see Python section below.

+

NOTE: Latest PyTorch requires Python 3.8 or later.

From cb3424b9e56ce6b19db5e83057655a1cbbb6b5f4 Mon Sep 17 00:00:00 2001 From: Svetlana Karslioglu Date: Mon, 15 Jul 2024 09:56:08 -0700 Subject: [PATCH 2/2] Update ROCm docs link --- _get_started/installation/linux.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/_get_started/installation/linux.md b/_get_started/installation/linux.md index ff29ec6e8575..e585c82648e1 100644 --- a/_get_started/installation/linux.md +++ b/_get_started/installation/linux.md @@ -1,7 +1,7 @@ # Installing on Linux {:.no_toc} -PyTorch can be installed and used on various Linux distributions. Depending on your system and compute requirements, your experience with PyTorch on Linux may vary in terms of processing time. 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](https://developer.nvidia.com/cuda-zone) [support](https://pytorch.org/tutorials/beginner/blitz/tensor_tutorial.html?highlight=cuda#cuda-tensors) or [ROCm](https://docs.amd.com) support. +PyTorch can be installed and used on various Linux distributions. Depending on your system and compute requirements, your experience with PyTorch on Linux may vary in terms of processing time. 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](https://developer.nvidia.com/cuda-zone) [support](https://pytorch.org/tutorials/beginner/blitz/tensor_tutorial.html?highlight=cuda#cuda-tensors) or [ROCm](https://rocm.docs.amd.com/) support. ## Prerequisites {: #linux-prerequisites} @@ -80,7 +80,7 @@ sudo apt install python3-pip #### No CUDA/ROCm -To install PyTorch via Anaconda, and do not have a [CUDA-capable](https://developer.nvidia.com/cuda-zone) or [ROCm-capable](https://docs.amd.com) system or do not require CUDA/ROCm (i.e. 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](https://developer.nvidia.com/cuda-zone) or [ROCm-capable](https://rocm.docs.amd.com/) system or do not require CUDA/ROCm (i.e. GPU support), in the above selector, choose OS: Linux, Package: Conda, Language: Python and Compute Platform: CPU. Then, run the command that is presented to you. #### With CUDA @@ -98,7 +98,7 @@ PyTorch via Anaconda is not supported on ROCm currently. Please use pip instead. #### No CUDA -To install PyTorch via pip, and do not have a [CUDA-capable](https://developer.nvidia.com/cuda-zone) or [ROCm-capable](https://docs.amd.com) system or do not require CUDA/ROCm (i.e. 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](https://developer.nvidia.com/cuda-zone) or [ROCm-capable](https://rocm.docs.amd.com/) system or do not require CUDA/ROCm (i.e. GPU support), in the above selector, choose OS: Linux, Package: Pip, Language: Python and Compute Platform: CPU. Then, run the command that is presented to you. #### With CUDA @@ -108,7 +108,7 @@ Then, run the command that is presented to you. #### With ROCm -To install PyTorch via pip, and do have a [ROCm-capable](https://docs.amd.com) system, in the above selector, choose OS: Linux, Package: Pip, Language: Python and the ROCm version supported. +To install PyTorch via pip, and do have a [ROCm-capable](https://rocm.docs.amd.com/) system, in the above selector, choose OS: Linux, Package: Pip, Language: Python and the ROCm version supported. Then, run the command that is presented to you. ## Verification @@ -151,7 +151,7 @@ For the majority of PyTorch users, installing from a pre-built binary via a pack 1. Install [Anaconda](#anaconda) or [Pip](#pip) 2. If you need to build PyTorch with GPU support a. for NVIDIA GPUs, install [CUDA](https://developer.nvidia.com/cuda-downloads), if your machine has a [CUDA-enabled GPU](https://developer.nvidia.com/cuda-gpus). - b. for AMD GPUs, install [ROCm](https://docs.amd.com), if your machine has a [ROCm-enabled GPU](https://docs.amd.com) + b. for AMD GPUs, install [ROCm](https://rocm.docs.amd.com/), if your machine has a [ROCm-enabled GPU](https://rocm.docs.amd.com/) 3. Follow the steps described here: [https://github.com/pytorch/pytorch#from-source](https://github.com/pytorch/pytorch#from-source) You can verify the installation as described [above](#linux-verification).