mdouze

###########################################
# serialization of indexes to byte arrays
###########################################

def serialize_index(index):
    """ convert an index to a numpy uint8 array  """
    writer = faiss.VectorIOWriter()
    faiss.write_index(index, writer)
    return faiss.vector_to_array(writer.data)

MikulasZelinka

"""
sort-of minimal end-to-end example of handling input sequences (sentences) of variable length in pytorch
the sequences are considered to be sentences of words, meaning we then want to use embeddings and an RNN
using pytorch stuff for basically everything in the pipeline of:
dataset -> data_loader -> padding -> embedding -> packing -> lstm -> unpacking (~padding)
based mostly on: https://github.com/HarshTrivedi/packing-unpacking-pytorch-minimal-tutorial
pytorch version 1.4.0
gist url: https://gist.github.com/MikulasZelinka/9fce4ed47ae74fca454e88a39f8d911a
"""

iamtekeste

Download Google Drive files with WGET

Example Google Drive download link:

https://docs.google.com/open?id=[ID]
To download the file with WGET you need to use this link:

https://googledrive.com/host/[ID]

Example WGET command:

lmars

# create a mongo app
flynn create --remote "" mongo

# create a release using the latest (at the time of writing) Docker MongoDB image
flynn -a mongo release add -f config.json "https://registry.hub.docker.com?name=mongo&id=216d9a0e82646f77b31b78eeb0e26db5500930bbd6085d5d5c3844ec27c0ca50"

# scale the server to one process. This may time out initially as the server pulls the image, but watch "flynn -a mongo ps" and it should come up.
flynn -a mongo scale server=1

# mongo should now be running in the cluster at mongo.discoverd:27017

allenanie

//For "# min" type
var searchCorpus = $('a.lecture-link').text();
var matches = searchCorpus.match(/(\d).+min/gm);
var bigResult = [];
for (index in matches) {bigResult.push(matches[index].match(/([\d]+)/g)[0]);}
var sum = 0;
for (index in bigResult) {sum = sum + parseInt(bigResult[index]);}

/*=============================================
=                 User Guide

alexlib

from PIL import Image
import os
import glob
import numpy as np


def crop(im, height, width):
    # im = Image.open(infile)
    imgwidth, imgheight = im.size
    rows = np.int(imgheight/height)

jeamland

import select
import socket
import sys

import objc
from PyObjCTools import AppHelper

objc.loadBundle("CoreBluetooth", globals(),
    bundle_path=objc.pathForFramework(u'/System/Library/Frameworks/IOBluetooth.framework/Versions/A/Frameworks/CoreBluetooth.framework'))

allenanie

<?php if ( ! defined('BASEPATH')) exit('No direct script access allowed');

require_once 'vendor/autoload.php';
use Aws\S3\S3Client;

final class AWS_S3 
{

	private static $client = null;

visenger

#!/bin/sh

# one way (older scala version will be installed)
# sudo apt-get install scala

#2nd way
sudo apt-get remove scala-library scala
wget http://www.scala-lang.org/files/archive/scala-2.11.4.deb
sudo dpkg -i scala-2.11.4.deb
sudo apt-get update

dariocravero

Create a Meteor app and put the client_/server_ files in a client/server directories. Also, create a public dir to save the uploaded files.