I think I found the bug.
My new hook looks like this:
def hook(module, input, output):
    print(module)
    print(len(input))
    print(input)

When in the forward contains the explicit variable name:
cell(None, (torch.zeros(1,1150), torch.zeros(1,115,10)), transformed_input=cell.ih(torch.ones(1,400)))

It outputs:

ONLSTMCell(
(ih): Sequential(
(0): Linear(in_features=400, out_features=4830, bias=True)
)
(hh): LinearDropConnect(in_features=1150, out_features=4830, bias=True)
)
2
(None, (tensor([[0., 0., 0.,  …, 0., 0., 0.]]), tensor([[[0., 0., 0.,  …, 0., 0., 0.],
[0., 0., 0.,  …, 0., 0., 0.],
[0., 0., 0.,  …, 0., 0., 0.],
…,
[0., 0., 0.,  …, 0., 0., 0.],
[0., 0., 0.,  …, 0., 0., 0.],
[0., 0., 0.,  …, 0., 0., 0.]]])))

When variable name in forward method is dropped:
cell(None, (torch.zeros(1,1150), torch.zeros(1,115,10)), cell.ih(torch.ones(1,400)))


ONLSTMCell(
(ih): Sequential(
(0): Linear(in_features=400, out_features=4830, bias=True)
)
(hh): LinearDropConnect(in_features=1150, out_features=4830, bias=True)
)
3
(None, (tensor([[0., 0., 0.,  …, 0., 0., 0.]]), tensor([[[0., 0., 0.,  …, 0., 0., 0.],
[0., 0., 0.,  …, 0., 0., 0.],
[0., 0., 0.,  …, 0., 0., 0.],
…,
[0., 0., 0.,  …, 0., 0., 0.],
[0., 0., 0.,  …, 0., 0., 0.],
[0., 0., 0.,  …, 0., 0., 0.]]])), tensor([[ 0.2503,  0.5609, -0.3321,  …,  0.2259, -0.2337, -0.3209]],
grad_fn=))