Merge pull request #132 from torch/container

refactoring all the common container code into nn.Container

6 files changed, 86 insertions, 176 deletions

diff --git a/Concat.lua b/Concat.lua
index c94808d..b0436a5 100644
--- a/Concat.lua
+++ b/Concat.lua
@@ -1,21 +1,11 @@
-local Concat, parent = torch.class('nn.Concat', 'nn.Module')
+local Concat, parent = torch.class('nn.Concat', 'nn.Container')
 
 function Concat:__init(dimension)
-   parent.__init(self)
-   self.modules = {}
+   parent.__init(self, dimension)
    self.size = torch.LongStorage()
    self.dimension = dimension
 end
 
-function Concat:add(module)
-   table.insert(self.modules, module)
-   return self
-end
-
-function Concat:get(index)
-   return self.modules[index]
-end
-
 function Concat:updateOutput(input)
    local outs = {}
    for i=1,#self.modules do
@@ -83,58 +73,6 @@ function Concat:accUpdateGradParameters(input, gradOutput, lr)
    end
 end
 
-function Concat:zeroGradParameters()
-   for _,module in ipairs(self.modules) do
-      module:zeroGradParameters()
-   end
-end
-
-function Concat:updateParameters(learningRate)
-   for _,module in ipairs(self.modules) do
-      module:updateParameters(learningRate)
-   end
-end
-
-function Concat:training()
-   for i=1,#self.modules do
-      self.modules[i]:training()
-   end
-end
-
-function Concat:evaluate()
-   for i=1,#self.modules do
-      self.modules[i]:evaluate()
-   end
-end
-
-function Concat:share(mlp,...)
-   for i=1,#self.modules do
-      self.modules[i]:share(mlp.modules[i],...);
-   end
-end
-
-function Concat:parameters()
-   local function tinsert(to, from)
-      if type(from) == 'table' then
-         for i=1,#from do
-            tinsert(to,from[i])
-         end
-      else
-         table.insert(to,from)
-      end
-   end
-   local w = {}
-   local gw = {}
-   for i=1,#self.modules do
-      local mw,mgw = self.modules[i]:parameters()
-      if mw then
-         tinsert(w,mw)
-         tinsert(gw,mgw)
-      end
-   end
-   return w,gw
-end
-
 function Concat:__tostring__()
    local tab = '  '
    local line = '\n'
diff --git a/Container.lua b/Container.lua
new file mode 100644
index 0000000..125ab98
--- /dev/null
+++ b/Container.lua
@@ -0,0 +1,80 @@
+-- This is code common to container modules, which are collections of
+-- smaller constituent modules like Parallel, Sequential, etc.
+local Container, parent =
+  torch.class('nn.Container', 'nn.Module')
+
+function Container:__init(...)
+    parent.__init(self, ...)
+    self.modules = {}
+end
+
+function Container:add(module)
+    table.insert(self.modules, module)
+    return self
+end
+
+function Container:get(index)
+    return self.modules[index]
+end
+
+function Container:size()
+    return #self.modules
+end
+
+function Container:zeroGradParameters()
+    for i=1,#self.modules do
+        self.modules[i]:zeroGradParameters()
+    end
+end
+
+function Container:updateParameters(learningRate)
+    for _,module in ipairs(self.modules) do
+        module:updateParameters(learningRate)
+    end
+end
+
+function Container:training()
+    for i=1,#self.modules do
+        self.modules[i]:training()
+    end
+end
+
+function Container:evaluate()
+    for i=1,#self.modules do
+        self.modules[i]:evaluate()
+    end
+end
+
+function Container:share(mlp, ...)
+    for i=1,#self.modules do
+        self.modules[i]:share(mlp.modules[i], ...);
+    end
+end
+
+function Container:reset(stdv)
+    for i=1,#self.modules do
+        self.modules[i]:reset(stdv)
+    end
+end
+
+function Container:parameters()
+    local function tinsert(to, from)
+        if type(from) == 'table' then
+            for i=1,#from do
+                tinsert(to,from[i])
+            end
+        else
+            table.insert(to,from)
+        end
+    end
+    local w = {}
+    local gw = {}
+    for i=1,#self.modules do
+        local mw,mgw = self.modules[i]:parameters()
+        if mw then
+            tinsert(w,mw)
+            tinsert(gw,mgw)
+        end
+    end
+    return w,gw
+end
diff --git a/Parallel.lua b/Parallel.lua
index 3057ba2..ef42723 100644
--- a/Parallel.lua
+++ b/Parallel.lua
@@ -1,4 +1,4 @@
-local Parallel, parent = torch.class('nn.Parallel', 'nn.Module')
+local Parallel, parent = torch.class('nn.Parallel', 'nn.Container')
 
 function Parallel:__init(inputDimension,outputDimension)
    parent.__init(self)
@@ -8,15 +8,6 @@ function Parallel:__init(inputDimension,outputDimension)
    self.outputDimension = outputDimension
 end
 
-function Parallel:add(module)
-   table.insert(self.modules, module)
-   return self
-end
-
-function Parallel:get(index)
-   return self.modules[index]
-end
-
 function Parallel:updateOutput(input)
    
    local modules=input:size(self.inputDimension)
@@ -99,36 +90,6 @@ function Parallel:accUpdateGradParameters(input, gradOutput, lr)
    end
 end
  
-function Parallel:zeroGradParameters()
-   for _,module in ipairs(self.modules) do
-      module:zeroGradParameters()
-   end
-end
-
-function Parallel:updateParameters(learningRate)
-   for _,module in ipairs(self.modules) do
-      module:updateParameters(learningRate)
-   end
-end
-
-function Parallel:training()
-   for i=1,#self.modules do
-      self.modules[i]:training()
-   end
-end
-
-function Parallel:evaluate()
-   for i=1,#self.modules do
-      self.modules[i]:evaluate()
-   end
-end
-
-function Parallel:share(mlp,...)
-   for i=1,#self.modules do
-      self.modules[i]:share(mlp.modules[i],...); 
-   end
-end
-
 function Parallel:parameters()
    local function tinsert(to, from)
       if type(from) == 'table' then
diff --git a/Sequential.lua b/Sequential.lua
index 97554b3..3288e6d 100644
--- a/Sequential.lua
+++ b/Sequential.lua
@@ -1,9 +1,4 @@
-local Sequential, parent = torch.class('nn.Sequential', 'nn.Module')
-
-function Sequential:__init()
-   parent.__init(self)
-   self.modules = {}
-end
+local Sequential, _ = torch.class('nn.Sequential', 'nn.Container')
 
 function Sequential:add(module)
    if #self.modules == 0 then
@@ -24,14 +19,6 @@ function Sequential:insert(module, index)
    self.gradInput = self.modules[1].gradInput
 end
 
-function Sequential:size()
-   return #self.modules
-end
-
-function Sequential:get(index)
-   return self.modules[index]
-end
-
 function Sequential:updateOutput(input)
    local currentOutput = input
    for i=1,#self.modules do 
@@ -82,63 +69,6 @@ function Sequential:accUpdateGradParameters(input, gradOutput, lr)
    currentModule:accUpdateGradParameters(input, currentGradOutput, lr)
 end
 
-function Sequential:zeroGradParameters()
-  for i=1,#self.modules do
-     self.modules[i]:zeroGradParameters()
-  end
-end
-
-function Sequential:updateParameters(learningRate)
-   for i=1,#self.modules do
-      self.modules[i]:updateParameters(learningRate)
-   end
-end
-
-function Sequential:training()
-   for i=1,#self.modules do
-      self.modules[i]:training()
-   end
-end
-
-function Sequential:evaluate()
-   for i=1,#self.modules do
-      self.modules[i]:evaluate()
-   end
-end
-
-function Sequential:share(mlp,...)
-   for i=1,#self.modules do
-      self.modules[i]:share(mlp.modules[i],...); 
-   end
-end
-
-function Sequential:reset(stdv)
-   for i=1,#self.modules do
-      self.modules[i]:reset(stdv)
-   end
-end
-
-function Sequential:parameters()
-   local function tinsert(to, from)
-      if type(from) == 'table' then
-         for i=1,#from do
-            tinsert(to,from[i])
-         end
-      else
-         table.insert(to,from)
-      end
-   end
-   local w = {}
-   local gw = {}
-   for i=1,#self.modules do
-      local mw,mgw = self.modules[i]:parameters()
-      if mw then
-         tinsert(w,mw)
-         tinsert(gw,mgw)
-      end
-   end
-   return w,gw
-end
 
 function Sequential:__tostring__()
    local tab = '  '
diff --git a/init.lua b/init.lua
index 0ab72a8..c556321 100644
--- a/init.lua
+++ b/init.lua
@@ -4,6 +4,7 @@ require('libnn')
 include('ErrorMessages.lua')
 include('Module.lua')
 
+include('Container.lua')
 include('Concat.lua')
 include('Parallel.lua')
 include('Sequential.lua')
diff --git a/test.lua b/test.lua
index 56298e0..3cf6a58 100644
--- a/test.lua
+++ b/test.lua
@@ -477,7 +477,7 @@ function nntest.WeightedEuclidean()
    local inj = math.random(13,5)
    local input = torch.Tensor(ini):zero()
    local module = nn.WeightedEuclidean(ini,inj)
-   
+
    local err = jac.testJacobian(module,input)
    mytester:assertlt(err,precision, 'error on state ')