joechai93

#include <iostream>
#include <string>
#include <vector>
#include <algorithm>
#include <numeric>
#include <cmath>

int main()
{
    std::vector<int> v = {1,4,6,3};

joechai93

#include <iostream>
#include <string>
#include <vector>
#include <algorithm>
#include <numeric>
#include <cmath>

int main()
{
    std::vector<int> A = {1,3, 2,4,7,6};

joechai93

#!/bin/bash
## This gist contains instructions about cuda v11.2 and cudnn 8.1 installation in Ubuntu 18.04 for PyTorch

#############################################################################################
##### forked by : https://gist.github.com/Mahedi-61/2a2f1579d4271717d421065168ce6a73 ########
#############################################################################################


### steps ####
# verify the system has a cuda-capable gpu

joechai93

# Copying from host to container

docker cp ~/Downloads/<filename> 0b2a63712e29:/home/joe/<filename>

# Running a live non-persistent container

docker container run --rm -ti ubuntu:latest /bin/bash  

# List and remove docker images

joechai93

#include <iostream>
#include <boost/function.hpp>
#include <boost/bind.hpp>
#include <boost/random/mersenne_twister.hpp>
#include <boost/random/uniform_real_distribution.hpp>
#include <boost/random/normal_distribution.hpp>

int main(int argc, char* argv[])
{
    size_t seed = 1234567890;

joechai93

Compile

npx hardhat compile

Run unit tests

npx hardhat test

Start local node

npx hardhat node

Deploy to Rinkeby