v0.0

docker/base.Dockerfile

@@ -2,7 +2,6 @@ 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
 
 # set default shell to bash
 SHELL ["/bin/bash", "-c"] 
@@ -10,6 +9,7 @@ SHELL ["/bin/bash", "-c"]
 RUN apt-get update && apt-get install -y --no-install-recommends \
     build-essential \
     curl \
+    nano \ 
     wget \
     p7zip-full \ 
     unzip \ 
@@ -30,40 +30,37 @@ RUN echo '%sudo ALL=(ALL) NOPASSWD:ALL' >> /etc/sudoers
 ENV CONDA_PATH=/opt/conda
 RUN wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -q && \ 
     bash Miniconda3-latest-Linux-x86_64.sh -b -p ${CONDA_PATH}  && \ 
-    ln -s ${CONDA_PATH}/etc/profile.d/conda.sh /etc/profile.d/conda.sh && \
-    echo "source conda init && conda activate ${conda_env}" >> /home/user/.bashrc && \
     rm -f Miniconda3-latest-Linux-x86_64.sh  && \ 
     chmod -R 777 ${CONDA_PATH}
 
 
-# activate conda base nev
-ENV PATH=${CONDA_PATH}/bin:$PATH
-
 # change to user and set working dir
 USER user
 WORKDIR /home/user
 
-RUN source ${CONDA_PATH}/bin/activate && conda init
+# initialize conda
+ENV PATH=${CONDA_PATH}/bin:$PATH
+RUN conda init
 
-# create conda environment and link it to jupyter
+# create conda environment and link it to jupyter kernel to use it in notebooks
 RUN conda create --quiet --yes -p "${CONDA_PATH}/envs/${conda_env}" python=${py_ver} ipython ipykernel jupyter && \
     conda clean --all -f -y && \ 
     "${CONDA_PATH}/envs/${conda_env}/bin/python" -m ipykernel install --user --name="${conda_env}"
 
+# activate the conda_env in bash terminals by default.
+# not the case for docker RUN commands as these run in separate shells.
+RUN echo "conda activate ${conda_env}" >> /home/user/.bashrc
 
-#set as default
-ENV CONDA_DEFAULT_ENV ${conda_env}
 
-
-# install pytorch 1.11
-RUN conda install numpy= && \
-    conda install pytorch=1.11 torchvision cudatoolkit -c pytorch && \
+# install pytorch 1.11 and dependencies in the conda env
+RUN source ${CONDA_PATH}/bin/activate && conda activate ${conda_env}&& \ 
+    conda install numpy=1.21.5 && \
+    conda install pytorch=1.11 torchvision=0.12.0 cudatoolkit=11.3.1 -c pytorch && \
     conda clean --all -f -y
 
-# install pip requirements
+# install pip requirements in the conda env
 COPY requirements.txt /tmp/
-RUN pip install --quiet --no-cache-dir -r /tmp/requirements.txt
-
+RUN  "${CONDA_PATH}/envs/${conda_env}/bin/pip" install --quiet --no-cache-dir -r /tmp/requirements.txt
 
 # keep container running (so no need to explicitly use interactive mode for starting the container)
 CMD tail -f /dev/null 
\ No newline at end of file

docker/gpulab-jupyterhub.Dockerfile

@@ -21,15 +21,14 @@ ENV PATH "${CONDA_DIR}/envs/${conda_env}/bin:${PATH}"
 # set to default
 ENV CONDA_DEFAULT_ENV ${conda_env}
 
-## install dependencies 
+## install dependencies
 
-# install pytorch 
-RUN conda install numpy && \
-    conda install pytorch=1.11 torchvision  cudatoolkit=11.3 -c pytorch && \
+# install pytorch 1.11
+RUN source ${CONDA_DIR}/bin/activate && conda activate ${conda_env}&& \ 
+    conda install numpy=1.21.5 && \
+    conda install pytorch=1.11 torchvision=0.12.0 cudatoolkit=11.3.1 -c pytorch && \
     conda clean --all -f -y
 
 # install pip requirements
 COPY requirements.txt /tmp/
-RUN "${CONDA_DIR}/envs/${conda_env}/bin/pip" install --quiet --no-cache-dir -r /tmp/requirements.txt
-
-
+RUN  "${CONDA_DIR}/envs/${conda_env}/bin/pip" install --quiet --no-cache-dir -r /tmp/requirements.txt
\ No newline at end of file

docker/requirements.txt

-pytorch-lightning
-matplotlib
+pytorch-lightning==1.6
+matplotlib==3.5.1
 requests
 pyyaml
-pandas
-scipy
-scikit-learn
-scikit-image
-seaborn
-wandb
+pandas==1.4.2
+scipy==1.8.0
+scikit-learn==1.0.2
+scikit-image==0.19.2
+seaborn==0.11.2
+wandb==0.12.15
 ipywidgets
 tqdm
 pre-commit
 pytest
-timm
-albumentations
+timm==0.5.4
+albumentations==1.1.0