最近看检测代码，经常会看到__setattr__和__getattr__这两个魔法属性，主要是对最后检测头的时候使用

我查询了一下：
__setattr__就等于在字典__dict__里面插入key和value
但是，__getattr__是在获取不到key的时候才用到这个，但为什么pytorch可以获取

import torch 
import torch.nn as nn
class Animal(nn.Module):
    def __init__(self,name,age) -> None:
        super(Animal,self).__init__()
        self.name = name 
        self.age = age 
        self.layer = nn.Conv2d(3,3,1,1)
        self.__setattr__("lay",self.layer)
        self.__setattr__("bb",'cc')
        print(self.__dict__) 
        #('lay', Conv2d(3, 3, kernel_size=(1, 1), stride=(1, 1)))]), 'name': '123', 'age': 12, 'bb': 'cc'}
    
    def forward(self,x):
        print( self.__getattr__('lay'))
        print(self.__getattr__('bb'))
        x = self.__getattr__('lay')(x)
        return x
cc = Animal('123',12)
x = torch.rand(1,3,3,3)
print(cc(x))

#   AttributeError: 'Animal' object has no attribute 'bb'

为什么layer可以，bb不可以呢，我查了下，原来pytorch 的nn.Module重写了这两个方法。。。进入这个Module方法进去可以看到有以下的方法

def __getattr__(self, name: str) -> Union[Tensor, 'Module']:
        if '_parameters' in self.__dict__:
            _parameters = self.__dict__['_parameters']
            if name in _parameters:
                return _parameters[name]
       .....
def __setattr__(self, name: str, value: Union[Tensor, 'Module']) -> None:
    def remove_from(*dicts_or_sets):
        for d in dicts_or_sets:
            if name in d:
                if isinstance(d, dict):
                    del d[name]
                else:
                    d.discard(name)

还有一种写法是这样

class IDAUp(nn.Module):
    '''
    IDAUp(channels[j], in_channels[j:], scales[j:] // scales[j])
    ida(layers, len(layers) -i - 2, len(layers))
    '''
    def __init__(self, o, channels, up_f):
        super(IDAUp, self).__init__()
        for i in range(1, len(channels)):
            c = channels[i]
            f = int(up_f[i])  
            proj = DeformConv(c, o)
            node = DeformConv(o, o)
            up = nn.ConvTranspose2d(o, o, f * 2, stride=f, 
                                    padding=f // 2, output_padding=0,
                                    groups=o, bias=False)
            fill_up_weights(up)
            setattr(self, 'proj_' + str(i), proj)
            setattr(self, 'up_' + str(i), up)
            setattr(self, 'node_' + str(i), node)
        
    def forward(self, layers, startp, endp):
        for i in range(startp + 1, endp):
            upsample = getattr(self, 'up_' + str(i - startp))
            project = getattr(self, 'proj_' + str(i - startp))

            layers[i] = upsample(project(layers[i]))
            node = getattr(self, 'node_' + str(i - startp))
            layers[i] = node(layers[i] + layers[i - 1])

setattr,delattr,getattr 到底干了什么？

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