尝试训练鲁棒CNN模型,其定义如下:
from keras.datasets import cifar10
from keras.utils import np_utils
from keras import metrics
from keras.models import Sequential
from keras.layers import Dense, Flatten, Conv2D, MaxPooling2D, LSTM, merge
from keras.layers import BatchNormalization
from keras import metrics
from keras.losses import categorical_crossentropy
from keras.optimizers import SGD
import pickle
import matplotlib.pyplot as plt
import numpy as np
from keras.preprocessing.image import ImageDataGenerator
from keras import layers
from keras.callbacks import EarlyStopping
def Robust_CNN():
model = Sequential()
model.add(Conv2D(256, (3, 3), activation='relu', padding='same', init='glorot_uniform', input_shape=(2,128,1)))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(1, 2), padding='valid', data_format=None))
model.add(layers.Dropout(.3))
model.add(Conv2D(128, (3, 3), activation='relu', init='glorot_uniform', padding='same'))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(1, 2), padding='valid', data_format=None))
model.add(layers.Dropout(.3))
model.add(Conv2D(64, (3, 3), activation='relu', init='glorot_uniform', padding='same'))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(1, 2), padding='valid', data_format=None))
model.add(layers.Dropout(.3))
model.add(Conv2D(64, (3, 3), activation='relu', init='glorot_uniform', padding='same'))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(1, 2), padding='valid', data_format=None))
model.add(layers.Dropout(.3))
model.add(Flatten())
model.add(Dense(128, activation='relu', init='he_normal'))
model.add(BatchNormalization())
model.add(Dense(11, activation='softmax', init='he_normal'))
return model
但是,在尝试执行此操作时,我收到一个NameError,指出name 'BatchNormalization'未定义。完整的错误消息如下所示:
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-11-8084d29438f8> in <module>
55 # >>>>>>>>>>>>>>>>>>>>> choose a model by un-commenting only one of the three <<<<<<<<<<<<<<<<<<<<<<<<<<<
56 #xx_shape = (2,128,1)
---> 57 models = Robust_CNN()
58 #models = CLDNN()
59 #models = resnet(xx_shape)
~\AppData\Local\Programs\Python\Python37\Scripts\FYP\Optimizing-Modulation-Classification-with-Deep-Learning-master\Optimizing-Modulation-Classification-with-Deep-Learning-master\Robust_CNN Model\model.py in Robust_CNN()
19 def Robust_CNN():
20
---> 21 model = Sequential()
22 model.add(Conv2D(256, (3, 3), activation='relu', padding='same', init='glorot_uniform', input_shape=(2,128,1)))
23 model.add(BatchNormalization())
NameError: name 'BatchNormalization' is not defined
即使我已经导入了BatchNormalization,似乎也弄不明白为什么会出现这种情况。
4条答案
按热度按时间vlju58qv1#
首先从
tensorflow.keras.layers
导入BatchNormalization
,然后运行代码:ebdffaop2#
把这个加到你的代码里-
from tensorflow.keras.layers import BatchNormalization
wb1gzix03#
e1xvtsh34#
导入批次规范化
从tensorflow .keras.layers导入批次规格化