Python qtype_load_data 예제들

예제 #1

파일: qtype_train_NoLSTM.py 프로젝트: ChunHungLiu/MLDS

# Parameters
batch_size = 200
nb_epoch = 20
verbose = 1
validation_split = 0.1
shuffle = True
show_accuracy = True

MODEL_ROOT = '../models/elephas/'
PREDICTION_ROOT = '../predictions/'

MODEL = 'qtype_noLSTM_batch_{}'.format(batch_size)

print 'Loading data...'
(X_train,Y_train),(X_test,Y_test) = qtype_load_data()
TEST_ID = '../Data/pkl/img_q_id_test'
TEST_ID_PKL = pickle.load(open(TEST_ID+'.pkl','rb'))
ids   = map(nameToId,[ TEST_ID_PKL[idx][1] for idx in range(len(TEST_ID_PKL)) ])

print 'Building model...'
model = Akar.keras_model(1)

#print 'Defining callbacks...'
#checkpoint = ModelCheckpoint('../models/elephas/checkpoint_'+MODEL+'.h5', monitor='val_loss', verbose=0, save_best_only=True, mode='auto')
#earlystopping = EarlyStopping(monitor='val_loss', patience=2, verbose=0)

print 'Start training...'
for epoch in [20,40,60,80,100]:
    model.fit( X_train, Y_train, batch_size=batch_size, nb_epoch=nb_epoch, verbose=verbose, callbacks=[],validation_split=validation_split, shuffle=shuffle,show_accuracy=show_accuracy)
    model.save_weights(MODEL_ROOT+MODEL+"_{}.h5".format(epoch))

예제 #2

파일: qtype_stopword_sixlayer_adagrad_train_NoLSTM.py 프로젝트: iammrhelo/MLDS

batch_size = 200
nb_epoch = 20
verbose = 1
validation_split = 0.1
shuffle = True
show_accuracy = True

MODEL_ROOT = '../models/elephas/'
PREDICTION_ROOT = '../predictions/'

MODEL = 'qtype_stop_sixlayeradagrad_noLSTM_batch_{}'.format(batch_size)

print 'Loading data...'
(X_train,Y_train),(X_test,Y_test) = stop_load_data()

Y_train = qtype_load_data()[0][1]

TEST_ID = '../Data/pkl/img_q_id_test'
TEST_ID_PKL = pickle.load(open(TEST_ID+'.pkl','rb'))
ids   = map(nameToId,[ TEST_ID_PKL[idx][1] for idx in range(len(TEST_ID_PKL)) ])

print 'Building model...'
model = Akar.keras_model(1)

#print 'Defining callbacks...'
#checkpoint = ModelCheckpoint('../models/elephas/checkpoint_'+MODEL+'.h5', monitor='val_loss', verbose=0, save_best_only=True, mode='auto')
#earlystopping = EarlyStopping(monitor='val_loss', patience=2, verbose=0)

print 'Start training...'
for epoch in [20,40,60,80,100,120,140,160,180,200]:
    model.fit( X_train, Y_train, batch_size=batch_size, nb_epoch=nb_epoch, verbose=verbose, callbacks=[],validation_split=validation_split, shuffle=shuffle,show_accuracy=show_accuracy)

예제 #3

batch_size = 200
nb_epoch = 20
verbose = 1
validation_split = 0.1
shuffle = True
show_accuracy = True

MODEL_ROOT = '../models/elephas/'
PREDICTION_ROOT = '../predictions/'

MODEL = 'qtype_stop_sixlayeradagrad_noLSTM_batch_{}'.format(batch_size)

print 'Loading data...'
(X_train, Y_train), (X_test, Y_test) = stop_load_data()

Y_train = qtype_load_data()[0][1]

TEST_ID = '../Data/pkl/img_q_id_test'
TEST_ID_PKL = pickle.load(open(TEST_ID + '.pkl', 'rb'))
ids = map(nameToId, [TEST_ID_PKL[idx][1] for idx in range(len(TEST_ID_PKL))])

print 'Building model...'
model = Akar.keras_model(1)

#print 'Defining callbacks...'
#checkpoint = ModelCheckpoint('../models/elephas/checkpoint_'+MODEL+'.h5', monitor='val_loss', verbose=0, save_best_only=True, mode='auto')
#earlystopping = EarlyStopping(monitor='val_loss', patience=2, verbose=0)

print 'Start training...'
for epoch in [20, 40, 60, 80, 100, 120, 140, 160, 180, 200]:
    model.fit(X_train,