lock some dependencies and add autobuild for base container

.gitlab-ci.yml

@@ -11,6 +11,8 @@ variables:
    DOCKER_DRIVER: overlay2
    CONTAINER_JUPYTERLAB_PYTORCH_IMAGE: $CI_REGISTRY_IMAGE/jupyterlab-pytorch:$CI_COMMIT_REF_SLUG
    CONTAINER_JUPYTERLAB_PYTORCH_RELEASE_IMAGE: $CI_REGISTRY_IMAGE/jupyterlab-pytorch:latest
+   CONTAINER_BASE_DL_IMAGE: $CI_REGISTRY_IMAGE/base-dl:$CI_COMMIT_REF_SLUG
+   CONTAINER_BASE_DL_RELEASE_IMAGE: $CI_REGISTRY_IMAGE/base-dl:latest
 
 
 before_script:
@@ -21,10 +23,24 @@ build_jupyterlab-pytorch:
   stage: build
   script:
     - docker pull $CONTAINER_JUPYTERLAB_PYTORCH_IMAGE || true
-    - docker build  --pull --cache-from $CONTAINER_JUPYTERLAB_PYTORCH_IMAGE --tag $CONTAINER_JUPYTERLAB_PYTORCH_IMAGE . -f gpulab-jupyterhub.Dockerfile
+    - docker build  --pull --cache-from $CONTAINER_JUPYTERLAB_PYTORCH_IMAGE --tag $CONTAINER_JUPYTERLAB_PYTORCH_IMAGE docker -f docker/gpulab-jupyterhub.Dockerfile
     - docker push $CONTAINER_JUPYTERLAB_PYTORCH_IMAGE
 
+build_base:
+  stage: build
+  script:
+    - docker pull $CONTAINER_BASE_DL_IMAGE || true
+    - docker build  --pull --cache-from $CONTAINER_BASE_DL_IMAGE --tag $CONTAINER_BASE_DL_IMAGE docker -f docker/base-dl.Dockerfile
+    - docker push $CONTAINER_BASE_DL_IMAGE
 
+  release_base_dl:
+  stage: release
+  script:
+    - docker pull $CONTAINER_BASE_DL_IMAGE
+    - docker tag $CONTAINER_BASE_DL_IMAGE $CONTAINER_BASE_DL_RELEASE_IMAGE
+    - docker push $CONTAINER_BASE_DL_RELEASE_IMAGE
+  only:
+    - main  
 release_pytorch:
   stage: release
   script:

docker/base.Dockerfile → docker/base-dl.Dockerfile

@@ -2,7 +2,7 @@ FROM nvidia/cuda:11.3.0-cudnn8-runtime-ubuntu20.04
 
 ARG conda_env=python39
 ARG py_ver=3.9
-ARG torch_version=1.11 # make sure this matches the CUDA version of the container
+ARG torch_version=1.11 
 
 # set default shell to bash
 SHELL ["/bin/bash", "-c"] 
@@ -56,7 +56,7 @@ ENV CONDA_DEFAULT_ENV ${conda_env}
 
 
 # install pytorch 1.11
-RUN conda install numpy= && \
+RUN conda install numpy=1.22.3 && \
     conda install pytorch=1.11 torchvision cudatoolkit -c pytorch && \
     conda clean --all -f -y
 

docker/gpulab-jupyterhub.Dockerfile

@@ -24,7 +24,7 @@ ENV CONDA_DEFAULT_ENV ${conda_env}
 ## install dependencies 
 
 # install pytorch 
-RUN conda install numpy && \
+RUN conda install numpy=1.22.3 && \
     conda install pytorch=1.11 torchvision  cudatoolkit=11.3 -c pytorch && \
     conda clean --all -f -y
 

docker/requirements.txt

-pytorch-lightning
+pytorch-lightning==1.6.1
 matplotlib
 requests
 pyyaml
@@ -7,10 +7,10 @@ scipy
 scikit-learn
 scikit-image
 seaborn
-wandb
+wandb==0.12.15
 ipywidgets
 tqdm
 pre-commit
 pytest
-timm
-albumentations
+timm==0.5.4
+albumentations==1.1.0