Keras輸出看起來比其它

Question

不同當我運行下面的代碼：

from keras.models import Sequential 
from keras.layers import Dense 
import numpy 
import time 

# fix random seed for reproducibility 
seed = 7 
numpy.random.seed(seed) 
# load dataset 

dataset = numpy.loadtxt("C:/Users/AQader/Desktop/Keraslearn/mammm.csv", delimiter=",") 
# split into input (X) and output (Y) variables 
X = dataset[:,0:5] 
Y = dataset[:,5] 

# create model 
model = Sequential() 
model.add(Dense(50, input_dim=5, init='uniform', activation='relu')) 
model.add(Dense(25, init='uniform', activation='tanh')) 
model.add(Dense(15, init='uniform', activation='tanh')) 
model.add(Dense(1, init='uniform', activation='sigmoid')) 

# Compile model 
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) 

# Fit the model 
model.fit(X, Y, nb_epoch=200, batch_size=20, verbose = 0) 
time.sleep(0.1) 

# evaluate the model 
scores = model.evaluate(X, Y) 
print("%s: %.2f%%" % (model.metrics_names[1], scores[1]*100)) 

我最終接收如下。

32/829 [>.............................] - ETA: 0sacc: 84.20% 

就是這樣。訓練半分鐘後只顯示一行。通過其他問題後，通常的輸出如下：

Epoch 1/20 
1213/1213 [==============================] - 0s - loss: 0.1760  
Epoch 2/20 
1213/1213 [==============================] - 0s - loss: 0.1840  
Epoch 3/20 
1213/1213 [==============================] - 0s - loss: 0.1816  
Epoch 4/20 
1213/1213 [==============================] - 0s - loss: 0.1915  
Epoch 5/20 
1213/1213 [==============================] - 0s - loss: 0.1928  
Epoch 6/20 
1213/1213 [==============================] - 0s - loss: 0.1964  
Epoch 7/20 
1213/1213 [==============================] - 0s - loss: 0.1948  
Epoch 8/20 
1213/1213 [==============================] - 0s - loss: 0.1971  
Epoch 9/20 
1213/1213 [==============================] - 0s - loss: 0.1899  
Epoch 10/20 
1213/1213 [==============================] - 0s - loss: 0.1957 

有誰可以告訴我什麼可能是錯誤的嗎？我是這個初學者，但這看起來不正常。請注意，「代碼」部分沒有錯誤。我的意思是0sacc是什麼顯示。我在Windows 7 64位機器上的Anaconda Environment Python 2.7中運行它。 8GB內存和酷睿i5第五代。

Answer 1

通過調用model.fit與verbose = 0你已經抑制了詳細的輸出。嘗試設置verbose = 1。