'Dense'类型的对象没有len（） [英] Object of Type 'Dense' has no len()

问题描述

我尝试创建一个CNN模型，但总是收到此错误消息。

I try to create a CNN model, but always get this error message.

错误：TypeError跟踪（最近一次调用）在（）----> 1模型= simple_conv_model（）5帧/usr/local/lib/python3.6/dist-packages/keras/engine/network.py在build_map中（张量，finished_nodes，nodes_in_progress，图层，node_index ，tensor_index）1345 1346＃传播到连接到该节点的所有先前的张量。 -> 1347 for i in range（len（node.inbound_layers））：1348 x = node.input_tensors [i] 1349 layer = node.inbound_layers [i] TypeError：密集类型的对象没有len（）

Error: TypeError Traceback (most recent call last) in () ----> 1 model = simple_conv_model() 5 frames /usr/local/lib/python3.6/dist-packages/keras/engine/network.py in build_map(tensor, finished_nodes, nodes_in_progress, layer, node_index, tensor_index) 1345 1346 # Propagate to all previous tensors connected to this node. -> 1347 for i in range(len(node.inbound_layers)): 1348 x = node.input_tensors[i] 1349 layer = node.inbound_layers[i] TypeError: object of type 'Dense' has no len()

这是模型：

def simple_conv_model():
        input_layer=layers.Input(shape=(64,64,3), name="input_layer")    
        model=layers.Conv2D(16,3, activation="relu", padding='same', name="first_block_conv", strides=(1,1)) (input_layer)
        model=layers.MaxPooling2D((2,2), name="first_block_pooling") (model)
        model=layers.BatchNormalization(name="first_block_bn") (model)

        model=layers.Conv2D(32,3, activation="relu", padding='same', name="second_block_conv", strides=(1,1)) (input_layer)
        model=layers.MaxPooling2D((2,2), name="second_block_pooling") (model)
        model=layers.BatchNormalization(name="second_block_bn") (model)

        model=layers.Conv2D(64,3, activation="relu", padding='same', name="third_block_conv", strides=(1,1)) (input_layer)
        model=layers.MaxPooling2D((2,2), name="third_block_pooling") (model)
        model=layers.BatchNormalization(name="third_block_bn") (model)

        model=layers.Flatten() (model)
        model=layers.Dense(16, activation="relu", name="dense_1") (model)
        model=layers.BatchNormalization() (model)
        model=layers.Dropout(0.5, name="drop_out_dense_1") (model)

        model=layers.Dense(4, activation="relu", name="dense_2") (model)

        model=layers.Dense(1, activation="linear") (model)

        model_cnn = Model(input_layer, model)
        model_cnn.compile(loss="mean_absolute_percentage_error", optimizer="adam")

        return model_cnn

    model = simple_conv_model()

推荐答案

我之前也遇到过这个问题，因为我是从tensorflow.python.ke导入库的ras。只是改为使用keras

I also face this problem before because I import library from tensorflow.python.keras. Just change to use keras instead

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