The two structures dont have the same nested structure... ...报错解决

 问题

运行报错：

TypeError: 'Specificity' does not have the same nested structure after one iteration.

The two structures don't have the same nested structure.

First structure: type=list str=[]
Second structure: type=list str=[<tf.Tensor 'regular_loss/while/Cast_1:0' shape=() dtype=float32>]
More specifically: The two structures don't have the same number of elements. First structure: type=list str=[]. Second structure: type=list str=[<tf.Tensor 'regular_loss/while/Cast_1:0' shape=() dtype=float32>]
Entire first structure:[]
Entire second structure:[.]

解决方法

 用tf.TensorArray()的方法声明“Specificity”变量，如：

Specificity = tf.TensorArray(tf.float32, size=nb_classes)

用对象的write()方法(形如:Specificity = Specificity.write())写入值；用stack()的方法提取值。

原因

函数中定义的“Specificity”在for循环中，属于变化的中间值。当用列表或者字典方法定义时，tf.2x默认为长度固定，所以出现迭代后长度（结构）不同的报错信息。当改用tf.TensorArray()方法时就可以顺利存储和调用循环中动态变化的值。

参考

https://www.tensorflow/guide/function

tensorflow2.0系列（4）: Eager Execution和Auto Graph_lxy_Alex的博客-CSDN博'