I have trained a binary classification model with CNN, and here is my code

model = Sequential()

model.add(Convolution2D(nb_filters, kernel_size[0], kernel_size[1],border_mode='valid',input_shape=input_shape))

model.add(Activation('relu'))

model.add(Convolution2D(nb_filters, kernel_size[0], kernel_size[1]))

model.add(Activation('relu'))

model.add(MaxPooling2D(pool_size=pool_size))

# (16, 16, 32)

model.add(Convolution2D(nb_filters*2, kernel_size[0], kernel_size[1]))

model.add(Activation('relu'))

model.add(Convolution2D(nb_filters*2, kernel_size[0], kernel_size[1]))

model.add(Activation('relu'))

model.add(MaxPooling2D(pool_size=pool_size))

# (8, 8, 64) = (2048)

model.add(Flatten())

model.add(Dense(1024))

model.add(Activation('relu'))

model.add(Dropout(0.5))

model.add(Dense(2)) # define a binary classification problem

model.add(Activation('softmax'))

model.compile(loss='categorical_crossentropy,optimizer='adadelta',

metrics=['accuracy'])

model.fit(x_train,y_train,batch_size=batch_size,nb_epoch=nb_epoch,verbose=1,validation_data=(x_test, y_test))

And here, I wanna get the output of each layer just like TensorFlow, how can I do that?