kirill-fedyanin

<%= check_box_tag :doc ,"value",!params[:doc].nil? %>

kirill-fedyanin

% Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100  6711  100  6711    0     0   6296      0  0:00:01  0:00:01 --:--:--  6296
tar=/bin/tar
version:
tar (GNU tar) 1.23
Copyright (C) 2010 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>.
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.

kirill-fedyanin

address_hints.js.coffee

вот это street = if suggestion.data.street_with_type then suggestion.data.street_with_type else '' можно заменить на это street = '' if !suggestion.data.street_with_type

вот это можно переформатить в одну-две строки, использую filter и join

kirill-fedyanin

require "mail"

PEOPLE = JSON.parse File.read("people")

# MAILER_SETUP =
Mail.defaults do
  delivery_method :smtp, {
    address: "smtp.yandex.ru",
    port: 465,
    user_name: "kirill@fedyanin.me",

kirill-fedyanin

#!/bin/sh
#
# Script for automatic setup of an IPsec/L2TP VPN server on Ubuntu LTS and Debian 8.
# Works on dedicated servers and any KVM- or Xen-based Virtual Private Server (VPS).
#
# DO NOT RUN THIS SCRIPT ON YOUR PC OR MAC! THIS IS MEANT TO BE RUN
# ON YOUR DEDICATED SERVER OR VPS!
#
# Copyright (C) 2014-2016 Lin Song
# Based on the work of Thomas Sarlandie (Copyright 2012)

kirill-fedyanin

def justify(text, width)
  words = text.split
  rows = split_rows(words, width)
  last_row = rows.pop
  text = rows.map{|row| justified_row(row, width)}.join("\n")
  [text, last_row.join(" ")].join("\n")
end

def justified_row(row, width)
  return row.join if row.length < 2

kirill-fedyanin

def justify(text, width)  
  text.split.reduce([[]]) do |lines, word|
    line = lines.last
    if (spaces = width - line.join(' ').length) > word.length
      line << word
    else
      spaces.times { |i| line[i % (line.count - 1)] += ' ' } if line.count > 1 
      lines << [word]  
    end
    lines

kirill-fedyanin

upstream puma {                                                                 
  server unix:///home/ct_cyrill/apps/sendit/tmp/sockets/puma.sock;              
}                                                                               
                                                                                
server {                                                                        
  listen 80 default_server deferred;                                            
  server_name localhost;                                        
                                                                                
  root /home/ct_cyrill/apps/sendit/public;                                      
  access_log /home/ct_cyrill/apps/sendit/log/nginx.access.log;                  

kirill-fedyanin

import keras
import numpy as np

model = keras.Sequential()
model.add(keras.layers.Dense(5, activation='sigmoid', input_shape=(1,)))
model.add(keras.layers.Dense(1, activation='sigmoid'))
model.compile('adadelta', 'mse', metrics=['accuracy'])

xs = np.array(range(1, 10))
ys = np.array([[0] for _ in range(5)] + [[1] for _ in range(4)])

kirill-fedyanin

const model = tf.sequential();
model.add(tf.layers.dense({ units: 5, activation: 'sigmoid', inputShape: [1]}));
model.add(tf.layers.dense({ units: 1, activation: 'sigmoid'}));
model.compile({loss: 'meanSquaredError', optimizer: 'adadelta'});
const xs = tf.tensor1d([1, 2, 3, 4, 5, 6, 7, 8, 9]);
const ys = tf.tensor1d([0, 0, 0, 0, 0, 1, 1, 1, 1]);
model.fit(xs, ys, {epochs: 1000}).then(h => {
   console.log("Loss after Epoch " + " : " + h.history.loss[0]);
   model.predict(xs).print();
});