#!/bin/bash

# Perform apt installs for bazel dependencies
sudo apt-get install build-essential openjdk-8-jdk python-dev zip unzip -y

# Tensorflow dependencies
sudo apt-get install python-numpy python-scipy python-pip python-wheel -y
sudo apt-get install python-enum32 python-mock python-h5py -y
sudo apt-get install python3-dev python3-numpy python3-scipy python3-pip python3-wheel -y
sudo apt-get install python3-mock python3-h5py -y
# mlocate will be used to locate libraries needed by TF
sudo apt-get install mlocate -y
sudo updatedb

# TF > 1.10 version requires keras libraries be present for the build
pip install keras_applications==1.0.4 --no-deps
pip install keras_preprocessing==1.0.2 --no-deps

pip3 install keras_applications==1.0.4 --no-deps
pip3 install keras_preprocessing==1.0.2 --no-deps
pip3 install enum34

# Build the deviceQuery script to allow us to pull out device information
cuda_location=/usr/local/cuda
cd $cuda_location/samples/1_Utilities/deviceQuery
sudo make -s

# Go out and get bazel
wget --no-check-certificate https://github.com/bazelbuild/bazel/releases/download/0.15.0/bazel-0.15.0-dist.zip

# unzip the bazel
unzip bazel-0.15.0-dist.zip -d bazel_build

cd bazel_build
./compile.sh

# Move bazel out to the main directory
mv output/bazel ../bazel

# clear up needed space
cd ..
rm -rf bazel_build
rm -rf bazel-0.15.2-dist.zip

# Bazel is done, next we need tensorflow

git clone --single-branch -b v1.12.0 https://github.com/tensorflow/tensorflow

# Prepare the environment, helperscript automagically looks through the device
# and finds the libraries and CUDA information to pass to TF
source ./helperscript

# make sure tensorflow knows bazel exists
export PATH="$PATH:$(`pwd`)"

# configure the build of tensorflow
bash ./tensorflow/configure

# Move into Tensorflow and build it.... YAY
cd tensorflow
git apply ../tf_1.12.0_patch.patch
../bazel build --config=opt --config=cuda  --config=monolithic //tensorflow/tools/pip_package:build_pip_package
../bazel build --config=opt --config=cuda --config=monolithic //tensorflow:libtensorflow_cc.so