Keras ValueError:(';当前不支持会话中的某些键:%s';,dict#u键([';类模式';]))
我在分析keras模型时发现了这个post错误,它修改了tensorflow库 因此,我从链接中检查了Keras库代码。但是找不到类似于['class_mode']的东西来修改Keras库。接下来,我尝试在重新安装Keras后运行代码,但即使这样也不起作用 我用anaconda进口Kreas,也许我安装错了Keras ValueError:(';当前不支持会话中的某些键:%s';,dict#u键([';类模式';])),keras,Keras,我在分析keras模型时发现了这个post错误,它修改了tensorflow库 因此,我从链接中检查了Keras库代码。但是找不到类似于['class_mode']的东西来修改Keras库。接下来,我尝试在重新安装Keras后运行代码,但即使这样也不起作用 我用anaconda进口Kreas,也许我安装错了 有人能提出解决方案吗?删除class\u mode='classifical',它运行时class\u mode不是model.compile的参数,你到底想用它做什么? from kera
有人能提出解决方案吗?删除class\u mode='classifical',它运行时class\u mode不是model.compile的参数,你到底想用它做什么?
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD
from keras.datasets import mnist
import numpy
model = Sequential()
model.add(Dense(500,input_shape=(784,))) # 28*28=784
model.add(Activation('tanh')) # tanh
model.add(Dropout(0.5)) # 50% dropout
model.add(Dense(500)) # 500个
model.add(Activation('tanh'))
model.add(Dropout(0.5))
model.add(Dense(10))
model.add(Activation('softmax'))
sgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='categorical_crossentropy', optimizer=sgd, class_mode='categorical')
(X_train, y_train), (X_test, y_test) = mnist.load_data()
X_train = X_train.reshape(X_train.shape[0], X_train.shape[1] * X_train.shape[2])
X_test = X_test.reshape(X_test.shape[0], X_test.shape[1] * X_test.shape[2])
Y_train = (numpy.arange(10) == y_train[:, None]).astype(int)
Y_test = (numpy.arange(10) == y_test[:, None]).astype(int)
model.fit(X_train,Y_train,batch_size=200,epochs=50,shuffle=True,verbose=0,validation_split=0.3)
model.evaluate(X_test, Y_test, batch_size=200, verbose=0)
print("test set")
scores = model.evaluate(X_test,Y_test,batch_size=200,verbose=0)
print("")
print("The test loss is %f" % scores)
result = model.predict(X_test,batch_size=200,verbose=0)