From 262ec5a4ebb37c1a0a8cae2500020644505bd091 Mon Sep 17 00:00:00 2001 From: "Baumgartner, Michael" Date: Mon, 9 Jan 2023 09:51:47 +0100 Subject: [PATCH] update pytorch versions --- Dockerfile | 2 +- README.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/Dockerfile b/Dockerfile index a89760e..59906b4 100644 --- a/Dockerfile +++ b/Dockerfile @@ -13,7 +13,7 @@ #limitations under the License. # Contains pytorch, torchvision, cuda, cudnn -FROM nvcr.io/nvidia/pytorch:20.12-py3 +FROM nvcr.io/nvidia/pytorch:21.11-py3 ARG env_det_num_threads=6 ARG env_det_verbose=1 diff --git a/README.md b/README.md index 89774ec..db48bef 100644 --- a/README.md +++ b/README.md @@ -54,7 +54,7 @@ When running a training inside the container it is necessary to [increase the sh 1. Install CUDA (>10.1) and cudnn (make sure to select [compatible versions](https://docs.nvidia.com/deeplearning/cudnn/support-matrix/index.html)!) 2. [Optional] Depending on your GPU you might need to set `TORCH_CUDA_ARCH_LIST`, check [compute capabilities](https://developer.nvidia.com/cuda-gpus) here. -3. Install [torch](https://pytorch.org/) (make sure to match the pytorch and CUDA versions!) (requires pytorch >1.7+) and [torchvision](https://github.com/pytorch/vision)(make sure to match the versions!). +3. Install [torch](https://pytorch.org/) (make sure to match the pytorch and CUDA versions!) (requires pytorch >1.10+) and [torchvision](https://github.com/pytorch/vision)(make sure to match the versions!). 4. Clone nnDetection, `cd [path_to_repo]` and `pip install -e .` 5. Set environment variables (more info can be found below): - `det_data`: [required] Path to the source directory where all the data will be located