How to Install Cudatoolkit in python environment in dockerfile

Question

I need to Install the Cudatoolkit in Docker file which is Python environment but cudatoolkit can only install by conda parameter.

We cant use conda in python.

Or can I create a anaconda environment in docker file and use python in anaconda?

Any solution !!

thanks in advance

Answer 1

In my case, I installed pytorch and torchvision through pip (from within the conda environment) and rest of the dependencies through conda

The final Dockerfile:

# Use nvidia/cuda image
FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04

# set bash as current shell
RUN chsh -s /bin/bash
SHELL ["/bin/bash", "-c"]

# install anaconda
RUN apt-get update
RUN apt-get install -y wget bzip2 ca-certificates libglib2.0-0 libxext6 libsm6 libxrender1 git mercurial subversion && \
        apt-get clean
RUN wget --quiet https://repo.anaconda.com/archive/Anaconda3-2020.02-Linux-x86_64.sh -O ~/anaconda.sh && \
        /bin/bash ~/anaconda.sh -b -p /opt/conda && \
        rm ~/anaconda.sh && \
        ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh && \
        echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc && \
        find /opt/conda/ -follow -type f -name '*.a' -delete && \
        find /opt/conda/ -follow -type f -name '*.js.map' -delete && \
        /opt/conda/bin/conda clean -afy

# set path to conda
ENV PATH /opt/conda/bin:$PATH


# setup conda virtual environment
COPY ./requirements.yaml /tmp/requirements.yaml
RUN conda update conda \
    && conda env create --name camera-seg -f /tmp/requirements.yaml

RUN echo "conda activate camera-seg" >> ~/.bashrc
ENV PATH /opt/conda/envs/camera-seg/bin:$PATH
ENV CONDA_DEFAULT_ENV $camera-seg

The requirements.yaml :

name: camera-seg
channels:
  - defaults
  - conda-forge
dependencies:
  - python=3.6
  - pip
  - numpy
  - pillow
  - yaml
  - pyyaml
  - matplotlib
  - jupyter
  - notebook
  - tensorboardx
  - tensorboard
  - protobuf
  - tqdm
  - pip:
    - torch
    - torchvision

Then I used the command docker build -t camera-seg . to build the container and PyTorch now recognises CUDA.