NameError：名称“X_train”未定义。这个错误也出现在剩余的代码中。请纠正这个

Question

from sklearn.model_selection import train_test_split  

data,Label = shuffle(M, label, random_state = 2)
labelled_data = [data, Label]
X,Y = [labelled_data[0],labelled_data[1]]

X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.4, random_state=4)
x_test, x_validation, y_test, y_validation=train_test_split(X_test, Y_test, test_size=0.5,
random_state=4)

X_train = X_train.reshape((X_train.shape[0],256,256,3))
x_validation = x_validation.reshape((x_validation.shape[0],256,256,3))

x_test =x_test.reshape((x_test.shape[0],256,256,3))
X_train = X_train.astype('float32')

x_validation = x_validation.astype('float32')
x_test = x_test.astype('float32')

X_train = X_train/255
x_validation = x_validation/255
x_test =x_test/255

from keras.utils import np_utils

Y_validation = np_utils.to_categorical(Y_train,8)
y_validation =np_utils.to_categorical(y_validation,8)
y_test =np_utils.to_categorical(y_test,8)

from keras.models import Sequential
from keras.layers import Activation, Dense

model = Sequential()
model.add(Dense(units=256,input_shape=(1000,),activation='relu'))
model.add(Dense(units=64,activation='tanh'))
model.add(Dense(units=8,activation='softmax'))
model.compile(loss='categorical_crossentropy', optimizer='sgd', 
metrics=['categorical_accuracy']) 
model.fit(X_train,Y_train,epochs=5,batch_size=32)
model.predict(x_test,batch_size=32)
return model


from keras.layers.convolutional import Convolution2D
model = Sequential()
model.add(convolution2D(filters=(6,3,3),input_shape=(256,256,1),activation='relu'))

from keras.layers.convolutional import MaxPooling2D
model = Sequential()
model.add(MaxPooling2D(pool_size=(2,2),strides=2))

from keras.layers import Dropout
model = Sequential()
model.add(Convolution2D(filters=6, nb_row=3, nb_col=3,subsample=(2,2),
    input_shape=(256, 256, 1,), activation='relu', border_mode='same'))
model.add(Dropout(0.1))
model.add(Flatten())
model.add(Dense(8, activation='softmax'))


model= fish_model()
print(model.summary())
history = model.fit(X_train,Y_train,validation_data=(x_validation, y_validation),epochs=5,batch_size=32)

Model: "sequential_42"

---

图层（类型）输出形状参数#

 dense_67 (Dense)             (None, 256)               256256    

---

 dense_68 (Dense)             (None, 64)                16448     

---

dense_69（密集）（无，8）520

 Total params: 273,224
 Trainable params: 273,224
  Non-trainable params: 0

---

无

NameError                                 Traceback (most recent call last)
 <ipython-input-131-ab439073340b> in <module>
       1 model= fish_model()
       2 print(model.summary())
 ----> 3 history = model.fit(X_train,Y_train,validation_data=(x_validation, y_validation),epochs=5,batch_size=32)

 NameError: name 'X_train' is not defined

我已经定义了 X_train，但是它显示了一个错误，比如 ir is not defined。 当我尝试测试准确性时，我也得到了相同的错误，例如未定义 x_test。

Answer 1

错误中显示的行号

---

'3'

---

与您发布的代码中的行号不匹配。

---

开始分块运行代码以获取错误的“真实”行号。例如，运行前 10 行代码，然后运行接下来的 10 行代码，或者运行第一个模块然后运行第二个模块。当您通过分块遇到错误时，行号应该是正确的，否则您可能会在运行块时发现错误，然后再到达代码末尾。