Yuki BAN yukiB

## file0.txt
Z = tanh(W_z * X)\\
F = \sigma(W_f * X)\\
O = \sigma(W_o * X)

## file0.cljs
(def data (atom {}))

...

;; pushState
(-> js/window .-history (.pushState #js {:data (pr-str data)} nil (str "/url"))))

;; popState
(set! (.-onpopstate js/window)
        #(when-not  (nil? (aget  % "state"))

## continuous.py（161~165行目）
    J = floor(dj**-1 * log2((N * dt) / s0))

    s = empty(int(J) + 1)

    for i in range(s.shape[0]):
        s[i] = s0 * 2**(i * dj)

## client.js
// client（web page）側
const {ipcRenderer} = require('electron')
console.log(ipcRenderer.sendSync('synchronous-message', 'ping')) // prints "pong"

ipcRenderer.on('asynchronous-reply', (event, arg) => {
  console.log(arg) // prints "pong"
})
ipcRenderer.send('asynchronous-message', 'ping')

## file0.txt
wheel install pyHook‑1.5.1‑cp36‑cp36m‑win_amd64.whl

## file0.txt
>>>  [i * 2 for i in range(10)]
[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]

## file0.txt
# モデル作成
model = Sequential()
model.add(InputLayer(input_shape=input_shape, name='input'))
model.add(Dense(nb_classes))
model.add(Activation('softmax', name='softmax'))

optimizer = SGD(lr=0.5)
model.compile(loss='categorical_crossentropy',
              optimizer=optimizer,
              metrics=['accuracy'])

## file0.txt

# input layer (8 x 8)
self.x = tf.placeholder(tf.float32, [None, 8, 8])

# flatten (64)
x_flat = tf.reshape(self.x, [-1, 64])

# fully connected layer (32)
W_fc1 = tf.Variable(tf.truncated_normal([64, 64], stddev=0.01))
b_fc1 = tf.Variable(tf.zeros([64]))

## file0.txt
_mysql_exceptions.OperationalError: (2006, 'MySQL server has gone away')

## file0.txt
team_list = ['A', 'B',...,'Z']
user_list = [('John', 14, 'C'), ...]
	(def data (atom {}))

	...

	;; pushState
	(-> js/window .-history (.pushState #js {:data (pr-str data)} nil (str "/url"))))

	;; popState
	(set! (.-onpopstate js/window)
	#(when-not (nil? (aget % "state"))
	J = floor(dj*-1 log2((N * dt) / s0))

	s = empty(int(J) + 1)

	for i in range(s.shape[0]):
	s[i] = s0 * 2*(i dj)
	// client（web page）側
	const {ipcRenderer} = require('electron')
	console.log(ipcRenderer.sendSync('synchronous-message', 'ping')) // prints "pong"

	ipcRenderer.on('asynchronous-reply', (event, arg) => {
	console.log(arg) // prints "pong"
	})
	ipcRenderer.send('asynchronous-message', 'ping')
	>>> [i * 2 for i in range(10)]
	[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
	# モデル作成
	model = Sequential()
	model.add(InputLayer(input_shape=input_shape, name='input'))
	model.add(Dense(nb_classes))
	model.add(Activation('softmax', name='softmax'))

	optimizer = SGD(lr=0.5)
	model.compile(loss='categorical_crossentropy',
	optimizer=optimizer,
	metrics=['accuracy'])

	# input layer (8 x 8)
	self.x = tf.placeholder(tf.float32, [None, 8, 8])

	# flatten (64)
	x_flat = tf.reshape(self.x, [-1, 64])

	# fully connected layer (32)
	W_fc1 = tf.Variable(tf.truncated_normal([64, 64], stddev=0.01))
	b_fc1 = tf.Variable(tf.zeros([64]))
	team_list = ['A', 'B',...,'Z']
	user_list = [('John', 14, 'C'), ...]