Dockerfile 1.4 KB

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  1. # Copyright (c) 2020 NVIDIA Corporation. All rights reserved.
  2. # To build the docker container, run: $ sudo docker build -t ai-science-cfd:latest --network=host .
  3. # To run: $ sudo docker run --rm -it --gpus=all -p 8888:8888 ai-science-cfd:latest
  4. # Finally, open http://127.0.0.1:8888/
  5. # Select Base Image
  6. FROM nvcr.io/nvidia/tensorflow:20.01-tf2-py3
  7. # Update the repo
  8. RUN apt-get update
  9. # Install required dependencies
  10. RUN apt-get install -y libsm6 libxext6 libxrender-dev git
  11. # Install required python packages
  12. RUN pip3 install opencv-python==4.1.2.30 pandas seaborn sklearn matplotlib scikit-fmm tqdm h5py gdown
  13. # TO COPY the data
  14. COPY English/ /workspace/
  15. #COPY English/python/jupyter_notebook/CFD /workspace/CFD/
  16. #COPY English/python/jupyter_notebook/Intro_to_DL /workspace/Intro_to_DL/
  17. #COPY English/Start_Here.ipynb /workspace/
  18. # Make a directory for Data
  19. RUN mkdir /workspace/python/jupyter_notebook/CFD/data
  20. # Copy the Python file for downloading dataset
  21. #COPY English/python/source_code/dataset.py /workspace/
  22. # This Installs All the Dataset
  23. #RUN python3 /workspace/dataset.py
  24. RUN python3 /workspace/python/source_code/dataset.py
  25. ## Uncomment this line to run Jupyter notebook by default
  26. #CMD jupyter notebook --ip 0.0.0.0 --port 8888 --allow-root
  27. CMD jupyter notebook --no-browser --allow-root --ip=0.0.0.0 --port=8888 --NotebookApp.token="" --notebook-dir=/workspace/python/jupyter_notebook/