It’s directly based on torch.sigmoid so no, it does not have bias parameter.
According to http://pytorch.org/docs/master/notes/extending.html 26,
what you can do is:
class SigmoidBias(nn.Module):
    def __init__(self, , bias=True):
        super(SigmoidBias, self).__init__()
        if bias:
            self.bias = nn.Parameter(torch.Tensor(output_features))
        else:
            # You should always register all possible parameters, but the
            # optional ones can be None if you want.
            self.register_parameter('bias', None)
        if self.bias is not None:
            self.bias.data.uniform_(-0.1, 0.1)

    def forward(self, input):
        outut = torch.sigmoid(output)
        if self.bias is not None:
            output += self.bias.unsqueeze(0).expand_as(output)
        return output