ValueError：检查目标时出错：预期density_1具有4维，但数组的形状为（5，1）

Question

train_datagen = ImageDataGenerator(rescale=1./255)

test_datagen = ImageDataGenerator(rescale=1./255)

train_generator = train_datagen.flow_from_directory(
        'dataset/train',
        target_size=(32, 32),
        batch_size = 478,
        class_mode='binary')

validation_generator = test_datagen.flow_from_directory(
        'dataset/valid',
        target_size=(32, 32),
        batch_size = 60,
        class_mode='binary')



model = Sequential()

model.add(layers.Conv2D(filters=6, kernel_size=(3, 3), activation='relu', input_shape=(32,32,3)))
model.add(layers.AveragePooling2D())

model.add(layers.Conv2D(filters=16, kernel_size=(3, 3), activation='relu'))
model.add(layers.AveragePooling2D())

model.add(layers.Flatten())

model.add(layers.Dense(units=120, activation='relu'))

model.add(layers.Dense(units=84, activation='relu'))

model.add(layers.Dense(units=2, activation = 'sigmoid'))

model.compile( loss = 'categorical_crossentropy',optimizer = 'adam', metrics = ['accuracy'])
model.summary()
model.fit_generator(
        train_generator,
        steps_per_epoch=478,
        epochs=100,
        validation_data=validation_generator,
        validation_steps=60)