September 24, 2019 06:41 · December 20, 2016 04:07 · November 17, 2016 02:01 · November 8, 2016 02:28 · November 15, 2016 12:12 · July 13, 2016 09:54
diff --git a/documentation b/documentation
 # -*- coding: utf-8 -*-

 class Hangul:
    BASE_CODE = 44032
    CHOSUNG = 588
    JUNGSUNG = 28

    # 초성 리스트. 00 ~ 18
    CHOSUNG_LIST = [
            'ㄱ', 'ㄲ', 'ㄴ', 'ㄷ', 'ㄸ', 'ㄹ', 'ㅁ', 'ㅂ', 'ㅃ',
 import csv
 import os

 def get_csv_writer(filename, rows, delimiter): 
    with open(filename, 'w') as csvfile:
        fieldnames = rows[0].keys()
        writer = csv.DictWriter(csvfile, fieldnames=fieldnames, delimiter=delimiter)
        writer.writeheader()
        for row in rows:
            try:
 # Note – this is not a bash script (some of the steps require reboot)
 # I named it .sh just so Github does correct syntax highlighting.
 #
 # This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5
 #
 # The CUDA part is mostly based on this excellent blog post:
 # http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/

 # Install various packages
 sudo apt-get update
 """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
 import numpy as np
 import cPickle as pickle
 import gym

 # hyperparameters
 H = 200 # number of hidden layer neurons
 batch_size = 10 # every how many episodes to do a param update?
 learning_rate = 1e-4
 gamma = 0.99 # discount factor for reward
	import csv
	import os

	def get_csv_writer(filename, rows, delimiter):
	with open(filename, 'w') as csvfile:
	fieldnames = rows[0].keys()
	writer = csv.DictWriter(csvfile, fieldnames=fieldnames, delimiter=delimiter)
	writer.writeheader()
	for row in rows:
	try:
	# Note – this is not a bash script (some of the steps require reboot)
	# I named it .sh just so Github does correct syntax highlighting.
	#
	# This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5
	#
	# The CUDA part is mostly based on this excellent blog post:
	# http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/

	# Install various packages
	sudo apt-get update
	""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
	import numpy as np
	import cPickle as pickle
	import gym

	# hyperparameters
	H = 200 # number of hidden layer neurons
	batch_size = 10 # every how many episodes to do a param update?
	learning_rate = 1e-4
	gamma = 0.99 # discount factor for reward