延长异常keras VGG16型号：self.assert_input_compatibility（X）抛出

Question

为了使用VGG16网络回归任务，我以下列方式将其扩展：

keras.applications.vgg16.VGG16(input_tensor=input_tensor, include_top=False) 
     x = model.output 
     x = Flatten()(x) 
     x = Dense(1024, activation='relu')(x) 
     x = Dropout(0.5)(x) 
     x = Dense(512,activation='relu')(x) 
     x = Dropout(0.5)(x) 
     x = Dense(256,activation='relu')(x) 
     x = Dropout(0.5)(x) 
     x = Dense(1)(x) 
     model = Model(model.input, x) 

这立即引发以下异常：

File "C:\Users\Ralph\Documents\GitHub\CarND-Behavioral-Cloning-P3\model.py", line 116, in <module> 
    tf.app.run() 
    File "C:\Users\Ralph\Miniconda3\envs\carnd-term1\lib\site-packages\tensorflow\python\platform\app.py", line 43, in run 
    sys.exit(main(sys.argv[:1] + flags_passthrough)) 
    File "C:\Users\Ralph\Documents\GitHub\CarND-Behavioral-Cloning-P3\model.py", line 101, in main 
    model = create_model() 
    File "C:\Users\Ralph\Documents\GitHub\CarND-Behavioral-Cloning-P3\model.py", line 60, in create_model 
    x = Dense(1024)(x) 
    File "C:\Users\Ralph\Miniconda3\envs\carnd-term1\lib\site-packages\keras\engine\topology.py", line 529, in __call__ 
    self.assert_input_compatibility(x) 
    File "C:\Users\Ralph\Miniconda3\envs\carnd-term1\lib\site-packages\keras\engine\topology.py", line 457, in assert_input_compatibility 
    if K.ndim(x) < ndim: 
    File "C:\Users\Ralph\Miniconda3\envs\carnd-term1\lib\site-packages\keras\backend\tensorflow_backend.py", line 396, in ndim 
    dims = x.get_shape()._dims 
AttributeError: 'function' object has no attribute 'get_shape' 
Press any key to continue . . . 

我是否必须更改体系结构，或者是否存在输入维推理问题？

Answer 1

我挖成本;当你调用set_learning_phase时，我相信这是最新版本中的一个错误;我提交了https://github.com/fchollet/keras/issues/5268和https://github.com/fchollet/keras/pull/5269

您可以回滚到1.2.0作为临时修复。

Answer 2

为我工作：

input_tensor = Input((3, 224, 224)) 
model = keras.applications.vgg16.VGG16(input_tensor=input_tensor, include_top=False) 
x = model.output 
x = model.output 
x = Flatten()(x) 
x = Dense(1024, activation='relu')(x) 
x = Dropout(0.5)(x) 
x = Dense(512,activation='relu')(x) 
x = Dropout(0.5)(x) 
x = Dense(256,activation='relu')(x) 
x = Dropout(0.5)(x) 
x = Dense(1)(x) 
model2 = Model(model.input, x) 
import numpy as np 
model2.predict(np.zeros((1, 3, 224,224))) 

输出：阵列（[[0.11504173]]，D型细胞= FLOAT32）