浅析PyTorch中nn.Linear的使用

Python  /  管理员 发布于 5年前   1067

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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

执行的操作是：

[140,100]×[100,50]=[140,50]

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