def __init__(self,type='nn'):
self.num_classes = 10
self.history = None
self.epoch = 10
self.verbose = True
self.info = Info()
if type == 'nn':
self.model = Sequential()
self.model.add(Dense(128,input_shape=(784,),activation='relu'))
self.model.add(Dense(128,activation='relu'))
self.model.add(Dense(self.num_classes,activation='softmax'))
elif type == 'cnn':
self.model = Sequential()
self.model.add(Conv2D(32, (3, 3), padding='same', input_shape=(32, 32, 3),activation='relu'))
#model.add(Activation('relu'))
self.model.add(Conv2D(32,(3, 3),activation='relu'))
#model.add(Activation('relu'))
self.model.add(MaxPooling2D(pool_size=(2, 2)))
#model.add(Dropout(0.25))
self.model.add(Conv2D(64, (3, 3), padding='same',activation='relu'))
#model.add(Activation('relu'))
self.model.add(Conv2D(64, (3,3),activation='relu'))
#model.add(Activation('relu'))
self.model.add(MaxPooling2D(pool_size=(2, 2)))
#model.add(Dropout(0.25))
self.model.add(Flatten())
self.model.add(Dense(512,activation='relu'))
#model.add(Activation('relu'))
#model.add(Dropout(0.5))
self.model.add(Dense(self.num_classes,activation='softmax'))
def __init__(self):
self.dim = 64
self.num_classes = 10
self.history = None
self.epoch = 1
input_shape = (32, 32, 3)
self.info = Info()
self.model = Sequential()
self.model.add(
Conv2D(32, (3, 3),
padding='same',
input_shape=input_shape,
activation='relu'))
self.model.add(Conv2D(32, (3, 3), activation='relu'))
self.model.add(MaxPooling2D(pool_size=(2, 2)))
self.model.add(Dropout(0.25))
self.model.add(Conv2D(64, (3, 3), padding='same', activation='relu'))
self.model.add(Conv2D(64, (3, 3), activation='relu'))
self.model.add(MaxPooling2D(pool_size=(2, 2)))
self.model.add(Dropout(0.25))
self.model.add(Flatten())
self.model.add(Dense(512, activation='relu'))
self.model.add(Dropout(0.5))
self.model.add(Dense(self.num_classes, activation='softmax'))
def __init__(self): self.dim = 64 self.num_classes = 10 self.history = None self.epoch = 10 self.info = Info() self.count = 0 self.model = Sequential() self.model.add(Dense(50,input_shape=(784,),activation='relu')) self.model.add(Dense(self.num_classes,activation='softmax')) self.y = self.model.output self.var_list = self.model.trainable_weights
def run():
pygame.init()
pygame.font.init()
set = Setting()
screen = pygame.display.set_mode((set.width, set.height))
info = Info(screen, set)
pygame.display.set_caption("TicTac")
blocks = Group()
winpage = WinPage(screen, set, info)
pausepage = PausePage(screen, set, info)
pages = {}
pages['Win'] = winpage
pages['Pause'] = pausepage
pages['Play'] = PlayPage(screen, set, info, blocks)
create_board(screen, set, blocks)
while True:
check_event(screen, set, blocks, info, pages)
update_screen(screen, set, blocks, info, pages)
def __init__(self):
self.dim = 64
self.num_classes = 10
self.history = None
self.epoch = 10
self.info = Info()
self.model = Sequential()
self.model.add(Dense(50, input_shape=(784, ), activation='relu'))
self.model.add(Dense(self.num_classes, activation='softmax'))
self.tbCallBack = TensorBoard(log_dir='./logs/mnist_drift/kal/',
histogram_freq=0,
write_graph=True,
write_grads=True,
write_images=True,
embeddings_freq=0,
embeddings_layer_names=None,
embeddings_metadata=None)