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
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