最近在用pycharm运行keras方面的代码时,会出现进度条多行打印问题,不知道是什么原因,但是我把代码放在Spyder上运行时,进度条是正常单行更新的,代码是深度学习的一个例程。在百度上也没搜到好的解决方法,恳请大家能帮忙解决这个问题,
from keras import layers,models
from keras.datasets import mnist
from keras.utils import to_categorical
(train_images,train_labels),(test_images,test_labels) = mnist.load_data()
train_images = train_images.reshape((60000,28,28,1))
train_images = train_images.astype('float32')/255
test_images = test_images.reshape((10000,28,28,1))
test_images = test_images.astype('float32')/255
train_labels = to_categorical(train_labels)
test_labels = to_categorical(test_labels)
model = models.Sequential()
model.add(layers.Conv2D(32,(3,3),activation='relu',input_shape=(28,28,1)))
model.add(layers.MaxPool2D(2,2))
model.add(layers.Conv2D(64,(3,3),activation='relu'))
model.add(layers.MaxPool2D(2,2))
model.add(layers.Conv2D(64,(3,3),activation='relu'))
model.add(layers.Flatten())
model.add(layers.Dense(64,activation='relu'))
model.add(layers.Dense(10,activation='softmax'))
model.summary()
model.compile(optimizer='rmsprop',
loss='categorical_crossentropy',
metrics=['accuracy'])
model.fit(train_images,train_labels,epochs=6,batch_size=64)
#test_loss,test_acc = model.evaluate(test_images,test_labels)
# print(test_loss,test_acc)