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######################################################################## | |
# Dockerfile for Oracle JDK 8 on Ubuntu 16.04 | |
# http://blog.h2o.ai/wp-content/uploads/2015/01/Dockerfile.txt | |
######################################################################## | |
# pull base image | |
FROM \ | |
ubuntu:16.04 | |
# maintainer details |
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package bigcache | |
import ( | |
"encoding/binary" | |
"testing" | |
"time" | |
"github.com/allegro/bigcache" | |
"github.com/coocood/freecache" | |
) |
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var json2csv = require('json2csv'); | |
var sanitize = require("sanitize-filename"); | |
var fs = require('fs'); | |
var users = require('./hipchat_export/users/list.json').users; | |
var room_list = require('./hipchat_export/rooms/list.json').rooms; | |
var escapeShell = function(cmd) { | |
return cmd.replace(/\//g, "-"); | |
}; |
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1. Install [Vegrant](https://www.vagrantup.com/downloads.html) | |
2. Download Vagrantfile `wget https://gist.githubusercontent.com/janisz/ce36ad51ee5fb6911786/raw/0503492c7226d95e8b5f801f4621982105578de8/Vagrantfile` | |
3. `vagrant up` | |
## Starter links | |
* http://www.wired.com/2013/03/google-borg-twitter-mesos/ | |
* https://manning-content.s3.amazonaws.com/download/2/c79863e-1021-4274-abcc-63b748548f24/Mesos_MEAP_ch1.pdf | |
* http://mesos.apache.org/documentation/latest/ |
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t a/package/opencv/Config.in b/package/opencv/Config.in | |
index 571309f..d725d44 100644 | |
--- a/package/opencv/Config.in | |
+++ b/package/opencv/Config.in | |
@@ -84,7 +84,12 @@ config BR2_PACKAGE_OPENCV_LIB_PHOTO | |
help | |
Include opencv_photo module into the OpenCV build. | |
-comment "opencv_python module requires numpy which is not yet available." | |
+config BR2_PACKAGE_OPENCV_LIB_PYTHON |
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install.packages("nnet") | |
# Funkcja trenuj膮ca, ktra bierze jako argument Y (wektor cyfr) | |
# oraz X (macierz obrazu) i zwraca obiekt sie膰 neuronow膮. | |
train_ANN = function(X,Y) { | |
library(nnet) # 艂adujemy bibliotek臋 | |
y <- class.ind(Y) # normalizujemy oczekiwane wyj艣膰ie do postacie macie偶y zer z jedn膮 jedynk膮 | |
ANN <- nnet(X,y,size=10,linout=T,maxit=1,MaxNWts=100000) # tworzymy i uczymy sie膰 | |
# aby zwi臋kszy膰 skuteczno艣膰 nauki nale偶y zwi臋kszy膰 liczb臋 iteracji (maxit), | |
# korzystne mo偶e te偶 by膰 zwi臋kszenie liczby neuron贸w (size) |
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#!/usr/bin/env python | |
# coding: utf-8 | |
from threading import Thread | |
from time import sleep | |
import subprocess | |
from libqtile.config import Key, Screen, Group, Drag, Click | |
from libqtile.command import lazy | |
from libqtile import layout, bar, widget, hook |
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OBJS := main.o | |
memo: $(OBJS) | |
$(CC) -o memo $(OBJS) | |
$(OBJS) : %.o : %.c | |
$(CC) -c $(CFLAGS) $< -o $@ -std=c99 | |
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## OPERACJE NA DANYCH ## | |
MOV arg1, arg2 - przesyla arg2 do arg1 | |
XCHG arg1, arg2 - zamienia warto艣ci argument贸w arg1 z arg2 | |
PUSH arg - umieszcza arg na stosie | |
POP arg - pobiera element ze stosu i umieszcza go w arg | |
PUSHA/POPA - umieszczenie/pobranie na stosie wszystkich rejestr贸w uniwersalnych | |
MOVZX/MOVSX rej, arg2 - rozciagniecie bez/ze znakiem arg2 i umieszczenie go w rej | |
BSWAP rej32 - odwr贸cenie kolejno艣ci bajt贸w | |
MOVBE arg1, arg2 - odwr. kolejnosci bajtow arg2 i przeslanie wyniku do arg1 | |
CMOV*** arg1, arg2 - warunkowe przeslanie arg2 do arg1 |