add CUDA 10.1 Docker image

.github/workflows/ci.yml

@@ -277,7 +277,7 @@ jobs:
     runs-on: [self-hosted, GPU]
     strategy:
       matrix:
-        cuda: ['10.2', '11.0']
+        cuda: ['10.1', '10.2', '11.0']
 
     steps:
     - uses: actions/checkout@v2
@@ -287,7 +287,9 @@ jobs:
         CUDA: ${{ matrix.cuda }}
       run: |
         # Check the install instructions on https://pytorch.org/ to keep these up-to-date.
-        if [[ $CUDA == '10.2' ]]; then
+        if [[ $CUDA == '10.1' ]]; then
+            echo "DOCKER_TORCH_VERSION='torch==1.7.1+cu101 -f https://download.pytorch.org/whl/torch_stable.html'" >> $GITHUB_ENV;
+        elif [[ $CUDA == '10.2' ]]; then
             echo "DOCKER_TORCH_VERSION='torch==1.7.1'" >> $GITHUB_ENV;
         elif [[ $CUDA == '11.0' ]]; then
             echo "DOCKER_TORCH_VERSION='torch==1.7.1+cu110 -f https://download.pytorch.org/whl/torch_stable.html'" >> $GITHUB_ENV;

CHANGELOG.md

@@ -15,6 +15,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   instead of an exception when lacking write permissions on an existing file lock.
   This makes it possible to use the `FileLock` class on a read-only file system.
 - Added a new learning rate scheduler: `CombinedLearningRateScheduler`. This can be used to combine different LR schedulers, using one after the other.
+- Added an official CUDA 10.1 Docker image.
 - Moving `ModelCard` and `TaskCard` abstractions into the main repository.
 
 ### Changed