Full SSH root access or a user with sudo privileges.
To connect to your server via SSH as the root user, use the following command:
root = true | |
[*] | |
charset = utf-8 | |
end_of_line = lf | |
indent_style = space | |
indent_size = 2 | |
insert_final_newline = true | |
trim_trailing_whitespace = true | |
tab_width = 8 |
# References: | |
# https://cmake.org/cmake/help/latest/command/add_custom_target.html | |
# https://samthursfield.wordpress.com/2015/11/21/cmake-dependencies-between-targets-and-files-and-custom-commands/ | |
# https://gist.github.com/socantre/7ee63133a0a3a08f3990 | |
# https://stackoverflow.com/questions/24163778/how-to-add-custom-target-that-depends-on-make-install | |
# https://stackoverflow.com/questions/30719275/add-custom-command-is-not-generating-a-target | |
# https://stackoverflow.com/questions/26024235/how-to-call-a-cmake-function-from-add-custom-target-command | |
# https://blog.csdn.net/gubenpeiyuan/article/details/51096777 | |
cmake_minimum_required(VERSION 3.10) |
Full documentation --> https://www.nongnu.org/pngpp/doc/0.2.9/
The libpng
it self, in Ubuntu 16.04 you can follow sudo apt install libpng12-dev
.
import torch | |
import torch.nn as nn | |
import torch.optim as optim | |
from torch.autograd import Variable | |
import torch.nn.functional as F | |
import matplotlib.pyplot as plt | |
import numpy as np |
Reference - https://www.eriksmistad.no/getting-started-with-google-test-on-ubuntu/
sudo apt-get install libgtest-dev
sudo apt-get install cmake # install cmake
cd /usr/src/gtest
sudo cmake CMakeLists.txt
#include <opencv2/core.hpp> | |
#include <opencv2/core/cuda.hpp> | |
#include <cuda_runtime.h> | |
#include <device_launch_parameters.h> | |
#include <iostream> | |
int main(int argc, const char * argv[]) | |
{ | |
cudaFree(0); // dummy call |
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
from __future__ import print_function | |
__author__ = 'maxim' | |
import numpy as np | |
import gensim | |
import string |
#include <iostream> | |
#include <algorithm> | |
using namespace std; | |
int find_substring(string str, string pattern) { | |
// Step 0. Should not be empty string | |
if( str.size() == 0 || pattern.size() == 0) | |
return -1; |
import tensorflow as tf | |
from tensorflow.python.client import timeline | |
from keras import backend as K | |
run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE) | |
run_metadata = tf.RunMetadata() | |
model = ... # A Keras model | |
fn = K.function(model.inputs, model.outputs, options=run_options, run_metadata=run_metadata) |