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

Question

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

Answer 1

No, ()() has no special meaning in Lua, it's just two call operators () together.
The operand is possibly a function that returns a function(or, a table that implements call metamethod). For example:
function foo()
return function() print(42) end
end
foo()() -- 42

Answer 2

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.

Answer 3

The first () calls the init function and the second () calls the call function
If the class doesn't posses either of these functions then the parent functions are called .
In the case of nn.Identity()() the nn.Identity has neither init function nor a call function hence the Identity parent nn.Module's init and call functions called .Attaching an illustration
require 'torch'
-- define some dummy A class
local A = torch.class('A')
function A:__init(stuff)
self.stuff = stuff
print('inside __init of A')
end
function A:__call__(arg1)
print('inside __call__ of A')
end
-- define some dummy B class, inheriting from A
local B,parent = torch.class('B', 'A')
function B:__init(stuff)
self.stuff = stuff
print('inside __init of B')
end
function B:__call__(arg1)
print('inside __call__ of B')
end
a=A()()
b=B()()
Output
inside __init of A
inside __call__ of A
inside __init of B
inside __call__ of B
Another code sample
require 'torch'
-- define some dummy A class
local A = torch.class('A')
function A:__init(stuff)
self.stuff = stuff
print('inside __init of A')
end
function A:__call__(arg1)
print('inside __call__ of A')
end
-- define some dummy B class, inheriting from A
local B,parent = torch.class('B', 'A')
b=B()()
Output
inside __init of A
inside __call__ of A