npx hardhat compile
npx hardhat test
npx hardhat node
#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; |
# 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 |
#!/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 |
#include <iostream> | |
#include <string> | |
#include <vector> | |
#include <algorithm> | |
#include <numeric> | |
#include <cmath> | |
int main() | |
{ | |
std::vector<int> A = {1,3, 2,4,7,6}; |
#include <iostream> | |
#include <string> | |
#include <vector> | |
#include <algorithm> | |
#include <numeric> | |
#include <cmath> | |
int main() | |
{ | |
std::vector<int> v = {1,4,6,3}; |