How to compile custom cpp files on Google Colab - c++

Question

I'm trying to replicate the result of this github repo using Google Colab since I don't want to install all the requirements on my local machine and to take advantage of the GPU on Google Colab
However, one of the things I need to do (as indicated in the repo's README) is to first compile a cpp makefile. The instruction of the makefile is included below. Obvious I can't follow this instruction since I don't know Google Colab's directories of ncvv, cudalib and tensorflow library
cd latent_3d_points/external
with your editor modify the first three lines of the makefile to point to
your nvcc, cudalib and tensorflow library.
make
Is there a way for me to compile the files included in the makefile (because those functions are needed to run the model) either using the makefile directly or compile each cpp file individually? I included the content of the makefile below to avoid having you to click around in the repo looking for it
nvcc = /usr/local/cuda-8.0/bin/nvcc
cudalib = /usr/local/cuda-8.0/lib64
tensorflow = /orions4-zfs/projects/optas/Virt_Env/tf_1.3/lib/python2.7/site-packages/tensorflow/include
all: tf_approxmatch_so.so tf_approxmatch_g.cu.o tf_nndistance_so.so tf_nndistance_g.cu.o
tf_approxmatch_so.so: tf_approxmatch_g.cu.o tf_approxmatch.cpp
g++ -std=c++11 tf_approxmatch.cpp tf_approxmatch_g.cu.o -o tf_approxmatch_so.so -shared -fPIC -I $(tensorflow) -lcudart -L $(cudalib) -O2 -D_GLIBCXX_USE_CXX11_ABI=0
tf_approxmatch_g.cu.o: tf_approxmatch_g.cu
$(nvcc) -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11 -c -o tf_approxmatch_g.cu.o tf_approxmatch_g.cu -I $(tensorflow) -DGOOGLE_CUDA=1 -x cu -Xcompiler -fPIC -O2
tf_nndistance_so.so: tf_nndistance_g.cu.o tf_nndistance.cpp
g++ -std=c++11 tf_nndistance.cpp tf_nndistance_g.cu.o -o tf_nndistance_so.so -shared -fPIC -I $(tensorflow) -lcudart -L $(cudalib) -O2 -D_GLIBCXX_USE_CXX11_ABI=0
tf_nndistance_g.cu.o: tf_nndistance_g.cu
$(nvcc) -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11 -c -o tf_nndistance_g.cu.o tf_nndistance_g.cu -I $(tensorflow) -DGOOGLE_CUDA=1 -x cu -Xcompiler -fPIC -O2
clean:
rm tf_approxmatch_so.so
rm tf_nndistance_so.so
rm *.cu.o

Answer 1

You can use the bash like on your pc by adding %%bash in the colab's cells.
Example:
Cell one: write cpp file
%%writefile welcome.cpp
#include <iostream>
int main()
{
std::cout << "Welcome To AI with Ashok's Blog\n";
return 0;
}
Cell two: compile and run
%%bash
g++ welcome.cpp -o welcome
./welcome
You can also open the cpp file in colab's build-in text editor in order to enjoy correct highlights. It opens when you open a text file from the "Files" tab on the left and can be save with "ctr+s" shortcut.

Answer 2

You can install the required version of Cuda in google colab. For eg.
For Cuda 9.2 you can try
!apt-get --purge remove cuda nvidia* libnvidia-*
!dpkg -l | grep cuda- | awk '{print $2}' | xargs -n1 dpkg --purge
!apt-get remove cuda-*
!apt autoremove
!apt-get update
!wget https://developer.nvidia.com/compute/cuda/9.2/Prod/local_installers/cuda-repo-ubuntu1604-9-2-local_9.2.88-1_amd64 -O cuda-repo-ubuntu1604-9-2-local_9.2.88-1_amd64.deb
!dpkg -i cuda-repo-ubuntu1604-9-2-local_9.2.88-1_amd64.deb
!apt-key add /var/cuda-repo-9-2-local/7fa2af80.pub
!apt-get update
!apt-get install cuda-9.2
Similarly, you can find a way to install Cuda 8.2.
For gcc
!apt-get install -qq gcc-5 g++-5 -y
!ln -s /usr/bin/gcc-5
!ln -s /usr/bin/g++-5
!sudo apt-get update
!sudo apt-get upgrade
Then you can compile it or make it by running make, if your installation has a custom make file.
!make