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，
