Pytorch 实现自定义参数层的例子
注意，一般官方接口都带有可导功能，如果你实现的层不具有可导功能，就需要自己实现梯度的反向传递。
官方Linear层：
classLinear(Module):
def__init__(self,in_features,out_features,bias=True):
super(Linear,self).__init__()
self.in_features=in_features
self.out_features=out_features
self.weight=Parameter(torch.Tensor(out_features,in_features))
ifbias:
self.bias=Parameter(torch.Tensor(out_features))
else:
self.register_parameter('bias',None)
self.reset_parameters()
defreset_parameters(self):
stdv=1./math.sqrt(self.weight.size(1))
self.weight.data.uniform_(-stdv,stdv)
ifself.biasisnotNone:
self.bias.data.uniform_(-stdv,stdv)
defforward(self,input):
returnF.linear(input,self.weight,self.bias)
defextra_repr(self):
return'in_features={},out_features={},bias={}'.format(
self.in_features,self.out_features,self.biasisnotNone
)
实现view层
classReshape(nn.Module): def__init__(self,*args): super(Reshape,self).__init__() self.shape=args defforward(self,x): returnx.view((x.size(0),)+self.shape)
实现LinearWise层
classLinearWise(nn.Module):
def__init__(self,in_features,bias=True):
super(LinearWise,self).__init__()
self.in_features=in_features
self.weight=nn.Parameter(torch.Tensor(self.in_features))
ifbias:
self.bias=nn.Parameter(torch.Tensor(self.in_features))
else:
self.register_parameter('bias',None)
self.reset_parameters()
defreset_parameters(self):
stdv=1./math.sqrt(self.weight.size(0))
self.weight.data.uniform_(-stdv,stdv)
ifself.biasisnotNone:
self.bias.data.uniform_(-stdv,stdv)
defforward(self,input):
x=input*self.weight
ifself.biasisnotNone:
x=x+self.bias
returnx
以上这篇Pytorch实现自定义参数层的例子就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持毛票票。