build_model.py

def build_finetune_model(base_model, dropout, fc_layers, num_classes):
    for layer in base_model.layers:
        layer.trainable = False

    x = base_model.output
    x = GlobalAveragePooling2D()(x)
    
    for fc in fc_layers:
        # New FC layer, random init
        x = Dense(fc, activation='relu')(x) 
        x = Dropout(dropout)(x)

    # New softmax layer
    predictions = Dense(num_classes, activation='softmax')(x) 
    
    finetune_model = Model(inputs=base_model.input, outputs=predictions)

    return finetune_model

FC_LAYERS = [100, 50]
dropout = 0.5

finetune_model = build_finetune_model(base_model, 
                                      dropout=dropout, 
                                      fc_layers=FC_LAYERS, 
                                      num_classes=4)

Hello,

I get the TypeError: Inputs to a layer should be tensors. Got: <keras.layers.pooling.GlobalAveragePooling2D object at 0x0000022F5F9FA220>

Do you have any idea why?