#!/bin/bash #Script last updated 25-03-2022 #Script that seems to be able to build bazel/tf2 on Ubuntu 20.04 #I really deeply dislike the bazel build system which is bloated and obfuscated for no reason, just Google "NIH syndrome" #However Tensorflow2 is a great NN framework # See this video "How To Make Package Managers Cry" -> https://www.youtube.com/watch?v=NSemlYagjIU#t=19m0s echo "Check CUDA" ls /usr/local/cuda/extras/CUPTI/lib64 ls /usr/local/cuda ls /usr/local/cuda/lib64/ | grep libcudnn.so nvcc -V VERSION="2.8" #Get number of bytes in RAM RAM=`free | grep Mem | tr -s ' '| cut -f2 -d ' '` BazelPleaseSlowDown="--local_resources 2048,.5,1.0" if [ "$RAM" -gt "11286464" ]; then echo "More than 12GB"; BazelPleaseSlowDown=" " fi if [ "$RAM" -gt "15297500" ]; then echo "More than 16GB"; BazelPleaseSlowDown=" " fi if [ "$RAM" -gt "31861780" ]; then echo "More than 32GB"; BazelPleaseSlowDown=" " fi #Tensorflow is a great Neural network library that unfortunately is coupled to the terrible Bazel build system #This is a download and build script for Ubuntu 20.04, that should work building release 2.8 sudo apt-get install python3-dev python3-pip python3-venv python3-tk pip3 install -U --user pip numpy wheel packaging pip3 install -U --user keras_preprocessing --no-deps cd ~/Documents mkdir 3dParty cd 3dParty #wget https://github.com/bazelbuild/bazel/releases/download/4.2.1/bazel-4.2.1-installer-linux-x86_64.sh #chmod +x bazel-4.2.1-installer-linux-x86_64.sh #./bazel-4.2.1-installer-linux-x86_64.sh --user #r2.8 mkdir -p "$HOME/.bazel/bin" && cd "$HOME/.bazel/bin" && curl -fLO https://releases.bazel.build/4.2.1/release/bazel-4.2.1-linux-x86_64 && chmod +x bazel-4.2.1-linux-x86_64 #Create shared directory if [ -f ~/.bashrc ] then if cat ~/.bashrc | grep -q "BAZEL_CANCER" then echo "Bazel includes seem to be set-up.." else USER=`whoami` echo "#BAZEL_CANCER" >> ~/.bashrc echo "source $HOME/.bazel/bin/bazel-complete.bash" >> ~/.bashrc echo "export PATH=\"\$PATH:\$HOME/bin\"" >> ~/.bashrc source ~/.bashrc fi fi if [ ! -d tensorflow ] then git clone https://github.com/tensorflow/tensorflow.git fi cd tensorflow git pull git checkout r$VERSION #Make sure to check your target CPU and when asked used the correct -march= / -mtune= # for example for an old intel i7 -march=nehalem is used.. #https://gcc.gnu.org/onlinedocs/gcc/x86-Options.html echo "Answers to configure questions :" echo "/usr/bin/python3" echo "/usr/lib/python3/dist-packages" echo "cuda Y" echo "tensorrt Y" echo "CUDA 11.2" echo "CuDNN 8" echo "TensorRT 8" echo "/usr/local/cuda/,/usr/local/cuda/include/,/usr/local/cuda/bin/,/usr/local/cuda/lib64/,/usr/local/cuda/lib64/,/usr/local/tensorrt-8.2.3/,/usr/local/tensorrt-8.2.3/include/,/usr/local/tensorrt-8.2.3/lib/," echo "Compute capability 6.1 ( for GTX 1050 + cards )" #Attempt to inform the configure script on how to find the CUDA stuff.. export CUDNN_INSTALL_PATH=/usr/local/cuda/,/usr/local/cuda/include/,/usr/local/cuda/bin/,/usr/local/cuda/lib64/,/usr/local/cuda/lib64/,/usr/local/tensorrt-8.2.3/,/usr/local/tensorrt-8.2.3/include/,/usr/local/tensorrt-8.2.3/lib/ ./configure bazel clean --expunge #You should use CUDA 11.2 and cudnn-11.2-linux-x64-v8.1.1.33 and TensorRT 8.2.3 bazel build --config=opt --config=cuda --config=mkl --config=monolithic $BazelPleaseSlowDown //tensorflow/tools/pip_package:build_pip_package ./bazel-bin/tensorflow/tools/pip_package/build_pip_package ~/Documents/3dParty/ #To install #pip3 --user install ~/Documents/3dParty/tensorflow-2.4.0-cp36-cp36m-linux_x86_64.whl bazel build --config opt --config=cuda --config=monolithic //tensorflow/tools/lib_package:libtensorflow cp bazel-bin/tensorflow/tools/lib_package/libtensorflow.tar.gz ~/Documents/3dParty/libtensorflow-r$VERSION.tar.gz #Build tensorflow lite #https://www.tensorflow.org/lite/guide/build_cmake mkdir tflite_buld cd tflite_buld/ cmake ../tensorflow/lite cmake --build . -j echo "Please visit ~/Documents/3dParty/ to collect your tensorflow python3 wheel, and C Library.." echo "Will now use : python -c 'import tensorflow as tf;' to test your tensorflow" python -c 'import tensorflow as tf;' exit 0