From 4c4c03124bd246aa891dbb9c00c6bd8a03405796 Mon Sep 17 00:00:00 2001 From: Jane Xu Date: Thu, 16 Sep 2021 13:22:02 -0700 Subject: [PATCH] Remove old references to 9.2 in documentation (#65059) Summary: Removes references in .rst and README.md and comments in the Dockerfile Pull Request resolved: https://github.com/pytorch/pytorch/pull/65059 Reviewed By: malfet Differential Revision: D30961110 Pulled By: janeyx99 fbshipit-source-id: 702a9a81bf08125ec4ac38bc656fc2c128c30018 --- README.md | 2 +- docker/pytorch/ubuntu_cpu_gpu/Dockerfile | 3 --- docs/source/notes/windows.rst | 4 +--- 3 files changed, 2 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index ed793fb8874..7ffdc2180b6 100644 --- a/README.md +++ b/README.md @@ -174,7 +174,7 @@ You will get a high-quality BLAS library (MKL) and you get controlled dependency Once you have [Anaconda](https://www.anaconda.com/distribution/#download-section) installed, here are the instructions. If you want to compile with CUDA support, install -- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) 9.2 or above +- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) 10.2 or above - [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v7 or above - [Compiler](https://gist.github.com/ax3l/9489132) compatible with CUDA Note: You could refer to the [cuDNN Support Matrix](https://docs.nvidia.com/deeplearning/cudnn/pdf/cuDNN-Support-Matrix.pdf) for cuDNN versions with the various supported CUDA, CUDA driver and NVIDIA hardwares diff --git a/docker/pytorch/ubuntu_cpu_gpu/Dockerfile b/docker/pytorch/ubuntu_cpu_gpu/Dockerfile index 7cb1d9309f2..f7a1af09302 100644 --- a/docker/pytorch/ubuntu_cpu_gpu/Dockerfile +++ b/docker/pytorch/ubuntu_cpu_gpu/Dockerfile @@ -5,20 +5,17 @@ # nvidia/cuda:11.2.1-cudnn8-devel-ubuntu18.04 # nvidia/cuda:10.2-cudnn8-devel-ubuntu18.04 # nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04 -# nvidia/cuda:9.2-cudnn7-devel-ubuntu18.04 # # Available MAGMA_CUDA_VERSION options (for GPU/CUDA builds): # magma-cuda112 # magma-cuda111 # magma-cuda102 # magma-cuda101 -# magma-cuda92 # # Available TORCH_CUDA_ARCH_LIST_VAR options (for GPU/CUDA builds): # "3.7+PTX;5.0;6.0;6.1;7.0;7.5;8.0;8.6" for CUDA 11.2/11.1 # "3.7+PTX;5.0;6.0;6.1;7.0;7.5;8.0" for CUDA 11.0 # "3.7+PTX;5.0;6.0;6.1;7.0;7.5" for CUDA 10.2/10.1 -# "3.7+PTX;5.0;6.0;6.1;7.0" for CUDA 9.2 # # Build image with CPU or GPU support with the following command: # nvidia-docker build -t ${CONTAINER_TAG} diff --git a/docs/source/notes/windows.rst b/docs/source/notes/windows.rst index 49689282339..92283521fec 100644 --- a/docs/source/notes/windows.rst +++ b/docs/source/notes/windows.rst @@ -24,9 +24,7 @@ MKL and MAGMA. Here are the steps to build with them. REM 2.5.3 (CUDA 10.1 10.2 11.0) x (Debug Release) REM 2.5.2 (CUDA 9.2 10.0 10.1 10.2) x (Debug Release) REM 2.5.1 (CUDA 9.2 10.0 10.1 10.2) x (Debug Release) - REM 2.5.0 (CUDA 9.0 9.2 10.0 10.1) x (Debug Release) - REM 2.4.0 (CUDA 8.0 9.2) x (Release) - set CUDA_PREFIX=cuda101 + set CUDA_PREFIX=cuda102 set CONFIG=release curl -k https://s3.amazonaws.com/ossci-windows/magma_2.5.4_%CUDA_PREFIX%_%CONFIG%.7z -o magma.7z 7z x -aoa magma.7z -omagma