# Ubuntu 18.04 Python3 with CUDA 11 and the following:
#  - Installs tf-nightly-gpu (this is TF 2.3)
#  - Installs requirements.txt for tensorflow/models

FROM nvidia/cuda:11.2.1-cudnn8-devel-ubuntu18.04 as base
ARG tensorflow_pip_spec="tf-nightly-gpu"
ARG local_tensorflow_pip_spec=""
ARG extra_pip_specs=""
ENV PIP_CMD="python3.9 -m pip"

# setup.py passes the base path of local .whl file is chosen for the docker image.
# Otherwise passes an empty existing file from the context.
COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}

# Pick up some TF dependencies
# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
# really be needed.
# In the future, add the following lines in a shell script running on the
# benchmark vm to get the available dependent versions when updating cuda
# version (e.g to 10.2 or something later):
# sudo apt-cache search cuda-command-line-tool
# sudo apt-cache search cuda-cublas
# sudo apt-cache search cuda-cufft
# sudo apt-cache search cuda-curand
# sudo apt-cache search cuda-cusolver
# sudo apt-cache search cuda-cusparse

# Needed to disable prompts during installation.
ENV DEBIAN_FRONTEND noninteractive


RUN apt-get update && apt-get install -y --no-install-recommends \
        libfreetype6-dev \
        libhdf5-serial-dev \
        libzmq3-dev \
        libpng-dev \
        pkg-config \
        software-properties-common \
        unzip \
        lsb-core \
        curl

# Python 3.9 related deps in this ppa.
RUN add-apt-repository ppa:deadsnakes/ppa


# Install / update Python and Python3
RUN apt-get install -y --no-install-recommends \
      python3.9 \
      python3-pip \
      python3.9-dev \
      python3-setuptools \
      python3.9-venv \
      python3.9-distutils \
      python3.9-lib2to3
      
# Upgrade pip, need to use pip3 and then pip after this or an error
# is thrown for no main found.
RUN ${PIP_CMD} install --upgrade pip
RUN ${PIP_CMD} install --upgrade distlib
# setuptools upgraded to fix install requirements from model garden.
RUN ${PIP_CMD} install --upgrade setuptools

# For CUDA profiling, TensorFlow requires CUPTI.
ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.2/lib64:$LD_LIBRARY_PATH

# See http://bugs.python.org/issue19846
ENV LANG C.UTF-8

# Add google-cloud-sdk to the source list
RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -

# Install extras needed by most models
RUN apt-get update && apt-get install -y --no-install-recommends \
      git \
      ca-certificates \
      wget \
      htop \
      zip \
      google-cloud-sdk

RUN ${PIP_CMD} install --upgrade pyyaml
RUN ${PIP_CMD} install --upgrade google-api-python-client==1.8.0
RUN ${PIP_CMD} install --upgrade google-cloud google-cloud-bigquery google-cloud-datastore mock


RUN ${PIP_CMD} install wheel
RUN ${PIP_CMD} install absl-py
RUN ${PIP_CMD} install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}

RUN ${PIP_CMD} install tfds-nightly
RUN ${PIP_CMD} install -U scikit-learn

# Install dependnecies needed for tf.distribute test utils
RUN ${PIP_CMD} install dill tblib portpicker

RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
RUN ${PIP_CMD} install -r /tmp/requirements.txt

RUN ${PIP_CMD} install tf-estimator-nightly
RUN ${PIP_CMD} install tensorflow-text-nightly
RUN ${PIP_CMD} install keras-nightly==2.7.0.dev2021082607

# RUN nvidia-smi

RUN nvcc --version


RUN pip freeze
