Cosmetics.

diff --git a/dagnn.lua b/dagnn.lua
index 9203264..14cd582 100755 (executable)
--- a/dagnn.lua
+++ b/dagnn.lua
@@ -29,32 +29,6 @@ function DAG:__init()
    self.node = { }
 end
 
-function DAG:createNode(nnm)
-   if not self.node[nnm] then
-      self:add(nnm) -- Add it to the object as a Container
-      local node = {}
-      node.succ = {}
-      node.pred = {}
-      node.index = #self.modules
-      self.node[nnm] = node
-   end
-end
-
--- The main use should be to add an edge between two modules, but it
--- can also add a full sequence of modules
-function DAG:connect(...)
-   self.sorted = nil
-   local prev
-   for _, nnm in pairs({...}) do
-      self:createNode(nnm)
-      if prev then
-         table.insert(self.node[nnm].pred, prev)
-         table.insert(self.node[prev].succ, nnm)
-      end
-      prev = nnm
-   end
-end
-
 -- Apply f on t recursively; use the corresponding element from args
 -- (i.e. same keys) as second parameter to f when available; return
 -- the results from f, organized in a similarly nested table.
@@ -70,36 +44,15 @@ function DAG:nestedApply(f, t, args)
    end
 end
 
-function DAG:setInput(i)
-   self.sorted = nil
-   self.inputModules = i
-   self:nestedApply(
-      function(nnm)
-         if #self.node[nnm].succ == 0 then
-            error('Input modules must have outgoing  edges.')
-         end
-         if #self.node[nnm].pred > 0 then
-            error('Input modules cannog have incoming edges.')
-         end
-      end,
-      self.inputModules
-   )
-end
-
-function DAG:setOutput(o)
-   self.sorted = nil
-   self.outputModules = o
-   self:nestedApply(
-      function(nnm)
-         if #self.node[nnm].pred == 0 then
-            error('Output module must have incoming edges.')
-         end
-         if #self.node[nnm].succ > 0 then
-            error('Output module cannot have outgoing edges.')
-         end
-      end,
-      self.outputModules
-   )
+function DAG:createNode(nnm)
+   if not self.node[nnm] then
+      self:add(nnm) -- Add it to the object as a Container
+      local node = {}
+      node.succ = {}
+      node.pred = {}
+      node.index = #self.modules
+      self.node[nnm] = node
+   end
 end
 
 function DAG:putInOrder()
@@ -149,6 +102,54 @@ function DAG:computeGradOutput(gradInputSucc)
    return gi
 end
 
+----------------------------------------------------------------------
+
+-- Connect a sequence of modules
+function DAG:connect(...)
+   self.sorted = nil
+   local prev
+   for _, nnm in pairs({...}) do
+      self:createNode(nnm)
+      if prev then
+         table.insert(self.node[nnm].pred, prev)
+         table.insert(self.node[prev].succ, nnm)
+      end
+      prev = nnm
+   end
+end
+
+function DAG:setInput(i)
+   self.sorted = nil
+   self.inputModules = i
+   self:nestedApply(
+      function(nnm)
+         if #self.node[nnm].succ == 0 then
+            error('Input modules must have outgoing  edges.')
+         end
+         if #self.node[nnm].pred > 0 then
+            error('Input modules cannog have incoming edges.')
+         end
+      end,
+      self.inputModules
+   )
+end
+
+function DAG:setOutput(o)
+   self.sorted = nil
+   self.outputModules = o
+   self:nestedApply(
+      function(nnm)
+         if #self.node[nnm].pred == 0 then
+            error('Output module must have incoming edges.')
+         end
+         if #self.node[nnm].succ > 0 then
+            error('Output module cannot have outgoing edges.')
+         end
+      end,
+      self.outputModules
+   )
+end
+
 function DAG:print()
    self:putInOrder()
 
@@ -159,6 +160,40 @@ end
 
 ----------------------------------------------------------------------
 
+function DAG:saveDot(filename)
+   local file = (filename and io.open(filename, 'w')) or io.stdout
+
+   file:write('digraph {\n')
+
+   file:write('\n')
+
+   for nnma, node in pairs(self.node) do
+      file:write(
+         '  '
+            .. node.index
+            .. ' [shape=box,label=\"' .. torch.type(nnma) .. '\"]'
+            .. '\n'
+      )
+
+      for _, nnmb in pairs(node.succ) do
+         file:write(
+            '  '
+               .. node.index
+               .. ' -> '
+               .. self.node[nnmb].index
+               .. '\n'
+         )
+      end
+
+      file:write('\n')
+   end
+
+   file:write('}\n')
+
+end
+
+----------------------------------------------------------------------
+
 function DAG:updateOutput(input)
    self:putInOrder()
 
@@ -259,37 +294,3 @@ function DAG:accGradParameters(input, gradOutput, scale)
       self:rethrowErrors(nnm, k, 'accGradParameters', node.input, self:computeGradOutput(node.gradInputSucc), scale)
    end
 end
-
-----------------------------------------------------------------------
-
-function DAG:dot(filename)
-   local file = (filename and io.open(filename, 'w')) or io.stdout
-
-   file:write('digraph {\n')
-
-   file:write('\n')
-
-   for nnma, node in pairs(self.node) do
-      file:write(
-         '  '
-            .. node.index
-            .. ' [shape=box,label=\"' .. torch.type(nnma) .. '\"]'
-            .. '\n'
-      )
-
-      for _, nnmb in pairs(node.succ) do
-         file:write(
-            '  '
-               .. node.index
-               .. ' -> '
-               .. self.node[nnmb].index
-               .. '\n'
-         )
-      end
-
-      file:write('\n')
-   end
-
-   file:write('}\n')
-
-end

diff --git a/test-dagnn.lua b/test-dagnn.lua
index 366e98f..462c287 100755 (executable)
--- a/test-dagnn.lua
+++ b/test-dagnn.lua
@@ -92,10 +92,9 @@ c = nn.Linear(10, 15)
 d = nn.CMulTable()
 e = nn.CAddTable()
 
-model:connect(a, b)
+model:connect(a, b, c)
 model:connect(b, nn.Linear(10, 15), nn.ReLU(), d)
 model:connect(d, e)
-model:connect(b, c)
 model:connect(c, d)
 model:connect(c, nn.Mul(-1), e)
 
@@ -110,4 +109,4 @@ output:uniform()
 print('Error = ' .. checkGrad(model, nn.MSECriterion(), input, output))
 
 print('Writing /tmp/graph.dot')
-model:dot('/tmp/graph.dot')
+model:saveDot('/tmp/graph.dot')