查看源码
Linear 的初始化部分:
class Linear(Module): ... __constants__ = ['bias'] 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)) if bias: self.bias = Parameter(torch.Tensor(out_features)) else: self.register_parameter('bias', None) self.reset_parameters() ...
需要实现的内容:
计算步骤:
@weak_script_method def forward(self, input): return F.linear(input, self.weight, self.bias)
返回的是:input * weight + bias
对于 weight
weight: the learnable weights of the module of shape :math:`(text{out_features}, text{in_features})`. The values are initialized from :math:`mathcal{U}(-sqrt{k}, sqrt{k})`, where :math:`k = frac{1}{text{in_features}}`
对于 bias
bias: the learnable bias of the module of shape :math:`(text{out_features})`. If :attr:`bias` is ``True``, the values are initialized from :math:`mathcal{U}(-sqrt{k}, sqrt{k})` where :math:`k = frac{1}{text{in_features}}`
实例展示
举个例子:
>>> import torch >>> nn1 = torch.nn.Linear(100, 50) >>> input1 = torch.randn(140, 100) >>> output1 = nn1(input1) >>> output1.size() torch.Size([140, 50])
张量的大小由 140 x 100 变成了 140 x 50
执行的 *** 作是:
[140,100]×[100,50]=[140,50]
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持考高分网。
欢迎分享,转载请注明来源:内存溢出
评论列表(0条)