How to use a learnable parameter in pytorch, constrained between 0 and 1?
I want to use a learnable parameter that only takes values between 0 and 1. How can I do this in pytorch?
Currently I am using:
self.beta = Parameter(torch.Tensor(1))
#initialize
zeros(self.beta)

But I am getting zeros and NaN for this parameter, as I train.

You can have a &quot;raw&quot; parameter taking any values, and then pass it through a sigmoid function to get a values in range (0, 1) to be used by your function.
For example:
class MyZeroOneLayer(nn.Module):
  def __init__(self):
    self.raw_beta = nn.Parameter(data=torch.Tensor(1), requires_grad=True)

  def forward(self):  # no inputs
    beta = torch.sigmoid(self.raw_beta)  # get (0,1) value
    return beta

Now you have a module with trainable parameter that is effectively in range (0,1)
