cafielo

from __future__ import print_function
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten, Activation
from keras.layers import Conv2D, MaxPooling2D
from keras import backend as K
from keras.layers.normalization import BatchNormalization

cafielo

from __future__ import print_function
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten, Activation
from keras.layers import Conv2D, MaxPooling2D
from keras import backend as K
from keras.layers.normalization import BatchNormalization

batch_size = 128

cafielo

if K.image_data_format() == 'channels_first':
    x_train = x_train.reshape(x_train.shape[0], 1, img_rows, img_cols)
    x_test = x_test.reshape(x_test.shape[0], 1, img_rows, img_cols)
    input_shape = (1, img_rows, img_cols)
else:
    x_train = x_train.reshape(x_train.shape[0], img_rows, img_cols, 1)
    x_test = x_test.reshape(x_test.shape[0], img_rows, img_cols, 1)
    input_shape = (img_rows, img_cols, 1)

x_train = x_train.astype('float32')

cafielo

model = Sequential()

model.add(Conv2D(32, (3, 3), input_shape=(28,28,1)))
model.add(Activation('relu'))
BatchNormalization(axis=-1)
model.add(Conv2D(32, (3, 3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2,2)))

BatchNormalization(axis=-1)

cafielo

model.compile(loss=keras.losses.categorical_crossentropy,
              optimizer=keras.optimizers.Adam(),
              metrics=['accuracy'])

model.fit(x_train, y_train,
          batch_size=batch_size,
          epochs=epochs,
          verbose=2,
          validation_data=(x_test, y_test))
score = model.evaluate(x_test, y_test, verbose=1)

cafielo

    func application(_ app: UIApplication, open url: URL, options: [UIApplicationOpenURLOptionsKey : Any] = [:]) -> Bool {
        let target = URLSchemeHandler.shared.parse(url: url)
        window?.rootViewController?.present(target, animated: true, completion: nil)
        return true
    }

cafielo

extension ViewController: UIGestureRecognizerDelegate {
    func gestureRecognizer(_ gestureRecognizer: UIGestureRecognizer, shouldReceive touch: UITouch) -> Bool {
        let isControllTapped = touch.view is UIControl
        return !isControllTapped
    }
}

cafielo

protocol Expandable {
    var isExpanded: Bool { get set }
}

class Bag: Expandable {
    var isExpanded = true
}

class CarryOn: Expandable {
    var isExpanded = true

cafielo

protocol Expandable: class {
    var isExpanded: Bool { get set }
}

cafielo

protocol Expandable: AnyObject {
    var isExpanded: Bool { get set }
}