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- # Copyright (c) 2020 NVIDIA Corporation. All rights reserved.
- # To build the docker container, run: $ sudo docker build -t ai-science-climate:latest --network=host .
- # To run: $ sudo docker run --rm -it --gpus=all --network=host -p 8888:8888 ai-science-climate:latest
- # Finally, open http://127.0.0.1:8888/
- # Select Base Image
- FROM nvcr.io/nvidia/tensorflow:21.05-tf2-py3
- # Update the repo
- RUN apt-get update -y
- # Install required dependencies
- RUN apt-get install -y libsm6 libxext6 libxrender-dev git nvidia-modprobe
- # Install required python packages
- RUN pip3 install opencv-python==4.1.2.30 pandas seaborn sklearn matplotlib scikit-fmm tqdm h5py gdown
- RUN pip3 install --upgrade pip
- RUN apt-get update -y
- RUN apt-get install -y git nvidia-modprobe
- RUN pip3 install jupyterlab
- # Install required python packages
- RUN pip3 install ipywidgets
- ##### TODO - From the Final Repo Changing this
- # TO COPY the data
- COPY English/ /workspace/
- # This Installs All the Dataset
- RUN python3 /workspace/python/source_code/dataset.py
- ## Uncomment this line to run Jupyter notebook by default
- CMD jupyter-lab --no-browser --allow-root --ip=0.0.0.0 --port=8888 --NotebookApp.token="" --notebook-dir=/workspace/python/jupyter_notebook/
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