python - Keras 模型输出形状为“（无，）”

Question

我的模型包括一个先前加载的模型，并给出“（无，）”的输出形状：

from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Activation, Dense, Input, Subtract, Multiply, Lambda

x = Input((158,))
y = model(x)
c = Subtract()([x,y])
c = Multiply()([c,c])
d = Lambda(lambda arg: tf.keras.backend.mean(arg,axis=1), output_shape = (None,1))
e = d(c)

new_model = Model(inputs = x, outputs = e)
new_model.summary()

Model: "model"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_1 (InputLayer)            [(None, 158)]        0                                            
__________________________________________________________________________________________________
model_1 (Model)                 (None, 158)          57310       input_1[0][0]                    
__________________________________________________________________________________________________
subtract (Subtract)             (None, 158)          0           input_1[0][0]                    
                                                                 model_1[1][0]                    
__________________________________________________________________________________________________
multiply (Multiply)             (None, 158)          0           subtract[0][0]                   
                                                                 subtract[0][0]                   
__________________________________________________________________________________________________
lambda (Lambda)                 (None,)              0           multiply[0][0]                   
==================================================================================================
Total params: 57,310
Trainable params: 57,310
Non-trainable params: 0
__________________________________________________________________________________________________

这个模型输出正确的值，但它可能会在我的下一步工作中产生问题，所以我想知道这个输出形状的含义，以及我是否必须纠正它（因为我没有看到这样的例子在线案例）。

编辑

具体来说，我不是在调查None价值，而是它没有说的事实，这(None,1)是同一件事吗？

例如，这个总结：

Layer (type)                 Output Shape              Param #
=================================================================
dense_1 (Dense)              (None, 2)                 4
_________________________________________________________________
dense_2 (Dense)              (None, 1)                 3
=================================================================
Total params: 7
Trainable params: 7
Non-trainable params: 0
_________________________________________________________________

来源：https ://machinelearningmastery.com/visualize-deep-learning-neural-network-model-keras/

标签： pythontensorflowkeras

Answer 1

这里没有代表你的batch size. 批量大小值是动态的，您稍后在.fit()定义它之前定义它，它不知道大小并且它仍然None意味着任何正整数值。

您可以阅读此处以更好地理解参数和值。