Prathyush SP kingspp

## numpy_transfer_over_kafka.py
"""
Requirements
1. Numpy
2. Pympler or a recursive sys.getsizeof()
3. PIL
"""

import numpy as np
from pympler.asizeof import asizeof
import json

## data_loader
'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

## tensorflow_finetune.py
"""
Example TensorFlow script for finetuning a VGG model on your own data.
Uses tf.contrib.data module which is in release v1.2
Based on PyTorch example from Justin Johnson
(https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c)

Required packages: tensorflow (v1.2)
Download the weights trained on ImageNet for VGG:
```
wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz

## tensorflow_custom_operation_gradient.py
# -*- coding: utf-8 -*-
"""
| **@created on:** 11/05/17,
| **@author:** Prathyush SP,
| **@version:** v0.0.1
|
| **Description:**
| DL Module Tests
| **Sphinx Documentation Status:** Complete
|

## logging.py
import os
import yaml
import logging.config
import logging
import coloredlogs

def setup_logging(default_path='logging.yaml', default_level=logging.INFO, env_key='LOG_CFG'):
    """
    | **@author:** Prathyush SP
    | Logging Setup

## requirements.txt
alabaster==0.7.9
appnope==0.1.0
audioread==2.1.4
Babel==2.3.4
beautifulsoup4==4.5.3
CherryPy==8.1.2
click==6.6
coloredlogs==6.1
configparser==3.5.0
coverage==4.3.4

## flake8.xml
<toolSet name="Code Checking">
  <tool name="Flake8" showInMainMenu="true" showInEditor="true" showInProject="true" showInSearchPopup="true" disabled="false" useConsole="true" showConsoleOnStdOut="false" showConsoleOnStdErr="false" synchronizeAfterRun="true">
    <exec>
      <option name="COMMAND" value="/usr/local/bin/flake8" />
      <option name="PARAMETERS" value="--max-complexity 10 $FilePath$" />
      <option name="WORKING_DIRECTORY" value="$ProjectFileDir$" />
    </exec>
    <filter>
      <option name="NAME" value="Filter 1" />
      <option name="DESCRIPTION" />

## dlink_router_config.js
/*
@author: Prathyush SP
@created on: 7/11/16
Prerequisites:
  1. PhantomJS
  2. CasperJS

Usage: casperjs dlink_router_config [Downstream Value]
*/
var casper = require('casper').create({

## client.html
<html>
    <body>
        <h1>I feel lonely</h1>

        <script type="text/javascript" src="//code.jquery.com/jquery-2.1.3.min.js"></script>
        <script type="text/javascript" src="//cdnjs.cloudflare.com/ajax/libs/socket.io/0.9.16/socket.io.min.js"></script>
        <script type="text/javascript" charset="utf-8">
            var socket = io.connect('http://' + document.domain + ':' + location.port);
            socket.on('connect', function() {
                socket.emit('connected');

## A Setup Snippets
Setup Snippets
	"""
	Requirements
	1. Numpy
	2. Pympler or a recursive sys.getsizeof()
	3. PIL
	"""

	import numpy as np
	from pympler.asizeof import asizeof
	import json
	"""
	Example TensorFlow script for finetuning a VGG model on your own data.
	Uses tf.contrib.data module which is in release v1.2
	Based on PyTorch example from Justin Johnson
	(https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c)

	Required packages: tensorflow (v1.2)
	Download the weights trained on ImageNet for VGG:
	```
	wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz
	# -- coding: utf-8 --
	"""
	\| @created on: 11/05/17,
	\| @author: Prathyush SP,
	\| @version: v0.0.1
	\|
	\| Description:
	\| DL Module Tests
	\| Sphinx Documentation Status: Complete
	\|
	import os
	import yaml
	import logging.config
	import logging
	import coloredlogs

	def setup_logging(default_path='logging.yaml', default_level=logging.INFO, env_key='LOG_CFG'):
	"""
	\| @author: Prathyush SP
	\| Logging Setup
	alabaster==0.7.9
	appnope==0.1.0
	audioread==2.1.4
	Babel==2.3.4
	beautifulsoup4==4.5.3
	CherryPy==8.1.2
	click==6.6
	coloredlogs==6.1
	configparser==3.5.0
	coverage==4.3.4
	<toolSet name="Code Checking">
	<tool name="Flake8" showInMainMenu="true" showInEditor="true" showInProject="true" showInSearchPopup="true" disabled="false" useConsole="true" showConsoleOnStdOut="false" showConsoleOnStdErr="false" synchronizeAfterRun="true">
	<exec>
	<option name="COMMAND" value="/usr/local/bin/flake8" />
	<option name="PARAMETERS" value="--max-complexity 10 $FilePath$" />
	<option name="WORKING_DIRECTORY" value="$ProjectFileDir$" />
	</exec>
	<filter>
	<option name="NAME" value="Filter 1" />
	<option name="DESCRIPTION" />
	/*
	@author: Prathyush SP
	@created on: 7/11/16
	Prerequisites:
	1. PhantomJS
	2. CasperJS

	Usage: casperjs dlink_router_config [Downstream Value]
	*/
	var casper = require('casper').create({
	<html>
	<body>
	<h1>I feel lonely</h1>

	<script type="text/javascript" src="//code.jquery.com/jquery-2.1.3.min.js"></script>
	<script type="text/javascript" src="//cdnjs.cloudflare.com/ajax/libs/socket.io/0.9.16/socket.io.min.js"></script>
	<script type="text/javascript" charset="utf-8">
	var socket = io.connect('http://' + document.domain + ':' + location.port);
	socket.on('connect', function() {
	socket.emit('connected');