overload operator __unm and __sub to support module chaining (#113)

* add operator support

* Update README.md

2 files changed, 60 insertions, 0 deletions

diff --git a/README.md b/README.md
index e11ee12..10c8ad0 100644
--- a/README.md
+++ b/README.md
@@ -51,6 +51,17 @@ To save the *graph* on file, specify the file name, and both a `dot` and `svg` f
 graph.dot(mlp.fg, 'MLP', 'myMLP')
 ```
 
+You can also use the `__unm__` and `__sub__` operators to replace all `__call__`:
+```lua
+h1 = - nn.Linear(20,10)
+h2 = h1
+     - nn.Tanh()
+     - nn.Linear(10,10)
+     - nn.Tanh()
+     - nn.Linear(10, 1)
+mlp = nn.gModule({h1}, {h2})
+```
+
 
 ### A network with 2 inputs and 2 outputs
 
@@ -72,6 +83,19 @@ gmod:updateGradInput({x1, x2}, {torch.rand(1), torch.rand(1)})
 graph.dot(gmod.fg, 'Big MLP')
 ```
 
+Alternatively, you can use `-` to make your code looks like the data flow:
+
+```lua
+h1 = - nn.Linear(20,20)
+h2 = - nn.Linear(10,10)
+hh1 = h1 - nn.Tanh() - nn.Linear(20,1)
+hh2 = h2 - nn.Tanh() - nn.Linear(10,1)
+madd = {hh1,hh2} - nn.CAddTable()
+oA = madd - nn.Sigmoid()
+oB = madd - nn.Tanh()
+gmod = nn.gModule( {h1,h2}, {oA,oB} )
+```
+
 <img src= "https://raw.github.com/koraykv/torch-nngraph/master/doc/mlp2.png" width="300px"/>
 
 
@@ -123,6 +147,23 @@ graph.dot(g.fg, 'Forward Graph')
 graph.dot(g.bg, 'Backward Graph')
 ```
 
+As your graph getting bigger and more complicated, the nested parentheses may become confusing. In this case, using `-` to chain the modules is a clearer and easier way:
+```lua
+input = - nn.Identity()
+L1 =  input 
+     - nn.Linear(10, 20) 
+     - nn.Tanh()
+L2 =  { input, L1 }
+     -  nn.JoinTable(1)
+     -  nn.Linear(30,60) 
+     -  nn.Tanh()
+L3 = { L1,L2 }
+     - nn.JoinTable(1)
+     - nn.Linear(80,160)
+     - nn.Tanh()
+g = nn.gModule({input},{L3})
+```
+
 <img src= "https://raw.github.com/koraykv/torch-nngraph/master/doc/mlp4_forward.png" width="300px"/>
 <img src= "https://raw.github.com/koraykv/torch-nngraph/master/doc/mlp4_backward.png" width="300px"/>
 
diff --git a/init.lua b/init.lua
index 455e1b0..0e354f6 100644
--- a/init.lua
+++ b/init.lua
@@ -58,4 +58,23 @@ function Criterion:__call__(...)
    return nn.ModuleFromCriterion(self)(...)
 end
 
+
+
+
+Module.__unm__ = function( obj )
+    return obj()
+end
+
+Module.__sub__ = function( prev, next )
+    return next(prev)
+end
+
+
+do
+    local Node = torch.getmetatable('nngraph.Node')
+    Node.__sub__ = function( prev, next )
+        return next(prev)
+    end
+end
+
 return nngraph