Is there special meaning for ()() syntax in Lua

I see this type of syntax a lot in some Lua source file I was reading lately, what does it mean, especially the second pair of brackets An example, line 8 in https://github.com/karpathy/char-rnn/blob/master/model/LSTM.lua

local LSTM = {}
function LSTM.lstm(input_size, rnn_size, n, dropout)
  dropout = dropout or 0 

  -- there will be 2*n+1 inputs
  local inputs = {}
  table.insert(inputs, nn.Identity()())  -- line 8
  -- ...

The source code of nn.Identity https://github.com/torch/nn/blob/master/Identity.lua

********** UPDATE **************

The ()() pattern is used in torch library 'nn' a lot. The first pair of bracket creates an object of the container/node, and the second pair of bracket references the depending node.

For example, y = nn.Linear(2,4)(x) means x connects to y, and the transformation is linear from 1*2 to 1*4. I just understand the usage, how it is wired seems to be answered by one of the answers below.

Anyway, the usage of the interface is well documented below. https://github.com/torch/nngraph/blob/master/README.md

Solution

In complement to Yu Hao's answer let me give some Torch related precisions:

nn.Identity() creates an identity module,
() called on this module triggers nn.Module __call__ (thanks to Torch class system that properly hooks up this into the metatable),
by default this __call__ method performs a forward / backward,
but here torch/nngraph is used and nngraph overrides this method as you can see here.

In consequence every nn.Identity()() calls has here for effect to return a nngraph.Node({module=self}) node where self refers to the current nn.Identity() instance.

Update: an illustration of this syntax in the context of LSTM-s can be found here:

local i2h = nn.Linear(input_size, 4 * rnn_size)(input)  -- input to hidden

If you’re unfamiliar with nngraph it probably seems strange that we’re constructing a module and already calling it once more with a graph node. What actually happens is that the second call converts the nn.Module to nngraph.gModule and the argument specifies it’s parent in the graph.