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# -*- coding: utf-8 -*-

import numpy as np
import chainer
from chainer import cuda, Function, gradient_check, Variable, optimizers, serializers, utils
from chainer import Link, Chain, ChainList
import chainer.functions as F
import chainer.links as L
import time
from matplotlib import pyplot as plt

kuc-arc-f

# encoding: utf-8

from keras.models import Sequential
from keras.layers.core import Dense, Activation
from keras.layers.recurrent import LSTM
from keras.optimizers import Adam
from keras.callbacks import EarlyStopping

import sys
import numpy as np

kuc-arc-f

# -*- coding: utf-8 -*- 
import requests
import json
import time
import sys
import gc
import traceback

import api_func
import com_func

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[Unit]
Description = tesorFlow Learning server

[Service]
ExecStart=/usr/bin/python /usr/local/yosoku_update/yosoku_update.py
Restart=always
Type=simple

[Install]
WantedBy=multi-user.target

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import tensorflow as tf
import json
from urllib2 import urlopen
import api_func

#ai_func
class ai_funcClass:
	def __init__(self):
		print ""

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#import tensorflow as tf
import json
from urllib2 import urlopen
import datetime
import threading
import time
import sys
import traceback

import api_func

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# -*- coding: utf-8 -*- 
# 日本語
from urllib2 import urlopen
import webapp2
import json
import os
import sys
import traceback
import com_func

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import tensorflow as tf

if __name__ == "__main__":
	# Model parameters
	W = tf.Variable([0.0], dtype=tf.float32)
	b = tf.Variable([0.0], dtype=tf.float32)
	# Model input and output
	x = tf.placeholder(tf.float32)
	y = tf.placeholder(tf.float32)
	linear_model = W*x + b

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# -*- coding: utf-8 -*- 
# 日本語
from urllib2 import urlopen
import webapp2
import json
import os
import sys
import traceback
import com_func

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<?php
// $file = 'dat/rest-data.json';

class AppConst {
	var $val01 = 'val01_###';
	var $mDir='dat';
	var $mExtName ='.json';
	var $mOK_CODE=1;
	var $mNG_CODE=0;