def __init__(self, num_ds_dim=4):
super(SigmoidFlow, self).__init__()
self.num_ds_dim = num_ds_dim
self.act_a = lambda x: nn_.softplus(x)
self.act_b = lambda x: x
self.act_w = lambda x: nn_.softmax(x, dim=2)
def __init__(self, in_dim, hidden_dim, out_dim):
super(DenseSigmoidFlow, self).__init__()
self.in_dim = in_dim
self.hidden_dim = hidden_dim
self.out_dim = out_dim
self.act_a = lambda x: nn_.softplus(x)
self.act_b = lambda x: x
self.act_w = lambda x: nn_.softmax(x, dim=3)
self.act_u = lambda x: nn_.softmax(x, dim=3)
self.u_ = Parameter(torch.Tensor(hidden_dim, in_dim))
self.w_ = Parameter(torch.Tensor(out_dim, hidden_dim))
self.reset_parameters()