我不断收到错误 TypeError: 'Tensor' object is not callable

Question

global_average_layer = keras.layers.GlobalAveragePooling2D()
feature_batch_average = global_average_layer(feature_batch)
print(feature_batch_average.shape)
flatten = keras.layers.Flatten()(base_model.layers[-1].output)
dense1 = keras.layers.Dense(256, activation = "relu")(flatten)
prediction_layer = keras.layers.Dense(3, activation = "softmax")(dense1)
x = base_model(inputs, training=False)
x = global_average_layer(x)
x = keras.layers.Dropout(0.5)(x)
outputs = prediction_layer(x)
model = keras.Model(inputs, outputs)
model.summary()

我不断收到 TypeError: 'Tensor' object is not callable at line outputs = prediction_layer(x) 。 任何线索我可能做错了什么？

编辑：添加了几行以明确我在做什么

base_model = keras.applications.DenseNet121(input_shape=IMG_SHAPE,
                                               include_top=False,
                                               weights='imagenet')

image_batch, label_batch = next(iter(train_dataset))
feature_batch = base_model(image_batch)
global_average_layer = keras.layers.GlobalAveragePooling2D()
feature_batch_average = global_average_layer(feature_batch)
print(feature_batch_average.shape)
flatten = keras.layers.Flatten()(base_model.layers[-1].output)
dense1 = keras.layers.Dense(256, activation = "relu")(flatten)
prediction_layer = keras.layers.Dense(3, activation = "softmax")(dense1)
x = base_model(inputs, training=False)
x = global_average_layer(x)
x = keras.layers.Dropout(0.5)(x)
outputs = prediction_layer(x)
model = keras.Model(inputs, outputs)
model.summary()

Answer 1

prediction_layer ，如第 5 行所述，将是Dense层的 output，因此只是Tensor而不是层。
您不需要base_model.layers[-1].output上的展平层，只需在x上进行即可。