ValueError：输入张量必须具有等级 4 TensorFlow

Question

i am using fashion_mnist images database (60,000 small square 28×28 pixel grayscale images) and i am trying to apply CNN-LSTM in cascading, this is the code i am using:

from tensorflow.keras.datasets import fashion_mnist

(x_train, y_train), (x_test, y_test) = fashion_mnist.load_data()
print("Shape of x_train: {}".format(x_train.shape))
print("Shape of y_train: {}".format(y_train.shape))
print()
print("Shape of x_test: {}".format(x_test.shape))
print("Shape of y_test: {}".format(y_test.shape))

# define CNN model
model = Sequential()
model.add(TimeDistributed(Conv2D(32, kernel_size=(3, 3),
             activation='relu',
             input_shape=(60000,28,28))))
model.add(TimeDistributed(Conv2D(64, (3, 3), activation='relu')))
model.add(TimeDistributed(MaxPooling2D(pool_size=(2, 2))))
model.add(TimeDistributed((Dropout(0.25))))
model.add(TimeDistributed(Flatten()))

## LSTM
model.add(LSTM(200, activation='relu', return_sequences=True))
model.add(Dense(128, activation='relu'))
model.compile(loss='categorical_crossentropy', optimizer='adam',
          metrics=['accuracy'])

##fitting model
 model.fit(x_train,y_train,epochs=5)
 test_loss, test_acc=model.evaluate(x_test,y_test)
 print('Loss: {0}-Acc:{1}')

 print(test_acc)

i get the error after running the fitting line, can any one help me solving the error.

Answer 1

Define an Input layer with a four-channel output instead of defining the input with Conv2D layer.