denguir

How to install CUDA / cuDNN / TensorRT on Ubuntu

Install NVIDIA drivers

Update & upgrade

sudo apt update && sudo apt upgrade

Remove previous NVIDIA installation

c-neto

#!/bin/bash

# Cloning all GitHub repositories belonging to a specific user provided as an argument.
#
# Command Execution Example:
#   ./clone-all-repos-github.sh <USERNAME>
#
# Arguments:
#   <USERNAME> GitHub username whose repositories will be cloned.
#

AdrianoPereira

import os
from bs4 import BeautifulSoup
import json


def get_filepaths(path):
	return [os.path.join(path, talk) for talk in os.listdir(path)]


def extract_questions_talk(filepath):

gnthibault

sudo add-apt-repository -y ppa:ubuntugis/ubuntugis-unstable
sudo apt update 
sudo apt upgrade
sudo apt-get install libgdal-dev libgdal1i

pip install --global-option=build_ext --global-option="-I/usr/include/gdal" GDAL

petitviolet

apiVersion: v1
kind: ConfigMap
metadata:
  name: nginx-conf
data:
  nginx.conf: |
    user nginx;
    worker_processes  3;
    error_log  /var/log/nginx/error.log;
    events {

thomasbnt

Here is an updated list of the colors that are currently implemented with a name. To using colors on discord.js, this is a typedef Colors, Colors.Aqua to get the Aqua color.

Name	Int value	Hex Code
Default	0	#000000
Aqua	1752220	#1ABC9C
DarkAqua	1146986	#11806A
Green	5763719	#57F287
DarkGreen	2067276	#1F8B4C

filipemeneses

const request = require('request-promise-native')
const cheerio = require('cheerio')
const login = ({user, pass}) => {
  let options = {
    method: 'POST',
    uri: 'https://siga.cps.sp.gov.br/aluno/login.aspx',
    headers: {
      'User-Agent': 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2228.0 Safari/537.36',
      'Content-Type': 'application/x-www-form-urlencoded',
      'Origin': 'https://siga.cps.sp.gov.br'

RyanAkilos

import numpy as np
from keras import backend as K
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution2D, MaxPooling2D
from keras.preprocessing.image import ImageDataGenerator
from sklearn.metrics import classification_report, confusion_matrix

#Start
train_data_path = 'F://data//Train'

ellisvalentiner

#!/usr/bin/env/python

import psycopg2
import os
from io import StringIO
import pandas as pd

# Get a database connection
dsn = os.environ.get('DB_DSN')  # Use ENV vars: keep it secret, keep it safe
conn = psycopg2.connect(dsn)

miguelmota

const EventEmitter = require('events')

class MyClass extends EventEmitter {
  constructor() {
    super() // required
    
    this.emit('event', 100)
  }
}