我在尝试可视化我的模型，但当我使用Keras的plot_model函数时，出现了错误，提示”‘InputLayer’对象不可迭代”。我附上了我的代码和错误信息，请帮助我解决这个问题。
model = tf.keras.models.Sequential([ tf.keras.layers.Conv2D(96, (5, 5), activation='relu', input_shape=(28, 28, 3), padding = 'same'), tf.keras.layers.Conv2D(96, (5, 5), activation='relu', padding = 'same'), tf.keras.layers.MaxPooling2D(2, 2), tf.keras.layers.Conv2D(256, (5, 5), activation='relu', padding = 'same'), tf.keras.layers.Conv2D(256, (5, 5), activation='relu', padding = 'same'), tf.keras.layers.MaxPooling2D(2, 2), tf.keras.layers.Conv2D(384, (3, 3), activation='relu', padding = 'same'), tf.keras.layers.Conv2D(384, (3, 3), activation='relu', padding = 'same'), tf.keras.layers.MaxPooling2D(2, 2), tf.keras.layers.Conv2D(256, (3, 3), activation='relu', padding = 'same'), tf.keras.layers.Conv2D(256, (3, 3), activation='relu', padding = 'same'), tf.keras.layers.Flatten(), tf.keras.layers.Dense(2304, activation='relu'), tf.keras.layers.Dense(2304, activation='relu'), tf.keras.layers.Dense(10, activation=tf.nn.softmax)])model.compile(optimizer=Adam(lr=0.001), loss='sparse_categorical_crossentropy', metrics=['acc'])plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)---------------------------------------------------------------------------TypeError Traceback (most recent call last)<ipython-input-92-2aa57a1383be> in <module>()----> 1 plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)1 frames/usr/local/lib/python3.6/dist-packages/keras/utils/vis_utils.py in plot_model(model, to_file, show_shapes, show_layer_names, rankdir) 130 'LR' creates a horizontal plot. 131 """--> 132 dot = model_to_dot(model, show_shapes, show_layer_names, rankdir) 133 _, extension = os.path.splitext(to_file) 134 if not extension:/usr/local/lib/python3.6/dist-packages/keras/utils/vis_utils.py in model_to_dot(model, show_shapes, show_layer_names, rankdir) 107 node_key = layer.name + '_ib-' + str(i) 108 if node_key in model._network_nodes:--> 109 for inbound_layer in node.inbound_layers: 110 inbound_layer_id = str(id(inbound_layer)) 111 dot.add_edge(pydot.Edge(inbound_layer_id, layer_id))TypeError: 'InputLayer' object is not iterable回答：
您混合使用了keras和tf.keras包的导入，这些包之间是不兼容的，您必须仅从一个包中进行所有相关导入。
