nn.PReLU(planes)

nn.PReLU(planes)

PReLU激活函数，内部源码实现

def __init__(self, num_parameters: int = 1, init: float = 0.25) -> None:
    self.num_parameters = num_parameters
    super(PReLU, self).__init__()
    self.weight = Parameter(torch.Tensor(num_parameters).fill_(init))

def forward(self, input: Tensor) -> Tensor:
    return F.prelu(input, self.weight)

def prelu(input, weight):
    # type: (Tensor, Tensor) -> Tensor
    r"""prelu(input, weight) -> Tensor

    Applies element-wise the function
    :math:`text{PReLU}(x) = max(0,x) + text{weight} * min(0,x)` where weight is a
    learnable parameter.

    See :class:`~torch.nn.PReLU` for more details.
    """
    if not torch.jit.is_scripting():
        if type(input) is not Tensor and has_torch_function((input,)):
            return handle_torch_function(prelu, (input,), input, weight)
    return torch.prelu(input, weight)

上边的公式搞到typora里就是如下形式：

weight这里是个可学习的参数，调用的时候nn.PReLU(planes)只输入了通道数，实现里将weight参数初始化为了0.25.

这和我们熟知的PRelu公式是一致的，