Design+a+class+named+People.+ 1+The+age+of+people+is+initialized+to+0+by+default+constructor.+ 2+T

Sure! Here's a class named People with the specified requirements:

class People:
    def __init__(self):
        self.age = 0

The above code defines a class called `People` with an `__init__` method that initializes the `age` attribute to 0. This means that when a new instance of the `People` class is created, the age of that person will be set to 0 by default.

Related question:
1. How can I modify the age of a person in the People class?
2. Can we add other attributes to the People class, such as name and address?

相关问题

cannot+import+name+read+from+partially+initialized+module+idlsave

这个错误通常出现在导入模块时，部分模块已经被初始化了。导致这个错误的原因可能是存在循环导入或者模块依赖关系不正确。解决这个问题有以下几种方法：

1. 检查循环导入：循环导入是指两个或多个模块之间相互导入，可以尝试重构代码，将导入语句移到函数内部或者使用延迟导入。

2. 检查模块依赖关系：确保模块之间的依赖关系正确，避免出现模块被重复地导入。

3. 更新模块版本：有时候这个问题可能是因为模块版本不兼容或者存在bug，尝试更新相关模块的版本，或者查看官方文档是否有类似的问题和解决方案。

如果以上方法都无法解决问题，请提供更多的上下文信息，例如完整的错误信息、代码片段等，以便我能更好地帮助您解决问题。

t = [torch.tensor(0)] * (self.cascades + 1)

This line of code creates a list of tensors with a length equal to the number of cascades in the model (self.cascades). The value of each tensor is initialized to 0.

The use of the asterisk (*) operator in front of a list creates a new list containing multiple copies of the same element. In this case, the same tensor with a value of 0 is copied multiple times, resulting in a list of tensors.

The purpose of this line of code is to create a list of tensors that will store the intermediate outputs of each cascade in the model during forward propagation. These tensors will be used later in the code to compute the final output of the model.