python - keras VGG19 add Input layer got graph disconnected error

Question

我有以下代码，我不明白为什么这是图形断开错误？我不知道出了什么问题。

def create_model_tl_attn_posInputOnly(input_shape):
    print("start creating model - transfer learning ...")

    emb = embed_encoding2d(input_shape[0], input_shape[1], input_shape[2]) # this is from another class

    img_input = Input(shape=input_shape)
    base_model = vgg19.VGG19(include_top=False, input_shape=input_shape, weights="imagenet")
    base_model.trainable = False
    x = base_model(img_input + emb)
    
    flat1 = Flatten()(x)
    class1 = Dense(1024, activation='relu')(flat1)
    dropout1 = Dropout(0.2)(class1)
    class2 = Dense(512, activation='relu')(dropout1)
    dropout2 = Dropout(0.2)(class2)
    
    output = Dense(num_classes, activation='softmax')(dropout2) 
    
    model = Model(inputs=img_input, outputs=output)
    
    return model

我更改为model = Model(inputs=base_model.inputs, outputs=output)，但仍然出现graph disconnected错误。

标签： pythonkeras

Answer 1

我更新代码如下，没有错误，但是我不知道是否input是和的总和img_input，emb如何在训练期间检查？

def create_model_tl_attn_posInputOnly(input_shape):
    print("start creating model - transfer learning ...")

    emb = embed_encoding2d(input_shape[0], input_shape[1], input_shape[2]) # this is from another class

    img_input = Input(shape=input_shape)
    base_model = vgg19.VGG19(include_top=False, input_shape=input_shape, weights="imagenet")
    base_model.trainable = False
    x = base_model(img_input + emb)
    x = base_model.layers[-1].output

    flat1 = Flatten()(x)
    class1 = Dense(1024, activation='relu')(flat1)
    dropout1 = Dropout(0.2)(class1)
    class2 = Dense(512, activation='relu')(dropout1)
    dropout2 = Dropout(0.2)(class2)
    
    output = Dense(num_classes, activation='softmax')(dropout2) 
    
    model = Model(inputs=base_model.inputs, outputs=output)
    
    return model