X-Git-Url: https://www.fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=test-dagnn.lua;h=462c287d0bfeb3486a0f79e4e463e48c64c659fc;hb=39ba70f10f81274998bc6786747a33e00b313fb4;hp=a41d8802931ec51f500a42ba4e2608540addf340;hpb=da6186a657b7563841416c42336e52937b76d67f;p=dagnn.git

diff --git a/test-dagnn.lua b/test-dagnn.lua
index a41d880..462c287 100755
--- a/test-dagnn.lua
+++ b/test-dagnn.lua
@@ -39,6 +39,8 @@ function checkGrad(model, criterion, input, target)
    model:backward(input, gradOutput)
    local analyticalGradParam = gradParams:clone()
 
+   local err = 0
+
    for i = 1, params:size(1) do
       local x = params[i]
 
@@ -54,23 +56,13 @@ function checkGrad(model, criterion, input, target)
 
       local ana = analyticalGradParam[i]
       local num = (loss1 - loss0) / (2 * epsilon)
-      local err
 
-      if num == ana then
-         err = 0
-      else
-         err = torch.abs(num - ana) / torch.abs(num)
+      if num ~= ana then
+         err = math.max(err, torch.abs(num - ana) / torch.abs(num))
       end
-
-      print(
-         'CHECK '
-            .. err
-            .. ' checkGrad ' .. i
-            .. ' analytical ' .. ana
-            .. ' numerical ' .. num
-      )
    end
 
+   return err
 end
 
 function printTensorTable(t)
@@ -84,13 +76,13 @@ function printTensorTable(t)
    end
 end
 
---               +- Linear(10, 10) -> ReLU ---> d --+
---              /                              /     \
---             /                              /       \
---  --> a --> b -----------> c --------------+         e -->
---                            \                       /
---                             \                     /
---                              +-- Mul(-1) --------+
+--               +-- Linear(10, 10) --> ReLU --> d --+
+--              /                              /      \
+--             /                              /        \
+--  --> a --> b -----------> c --------------+          e -->
+--                            \                        /
+--                             \                      /
+--                              +----- Mul(-1) ------+
 
 model = nn.DAG()
 
@@ -100,12 +92,11 @@ c = nn.Linear(10, 15)
 d = nn.CMulTable()
 e = nn.CAddTable()
 
-model:addEdge(a, b)
-model:addEdge(b, nn.Linear(10, 15), nn.ReLU(), d)
-model:addEdge(d, e)
-model:addEdge(b, c)
-model:addEdge(c, d)
-model:addEdge(c, nn.Mul(-1), e)
+model:connect(a, b, c)
+model:connect(b, nn.Linear(10, 15), nn.ReLU(), d)
+model:connect(d, e)
+model:connect(c, d)
+model:connect(c, nn.Mul(-1), e)
 
 model:setInput(a)
 model:setOutput(e)
@@ -115,4 +106,7 @@ local output = model:updateOutput(input):clone()
 
 output:uniform()
 
-checkGrad(model, nn.MSECriterion(), input, output)
+print('Error = ' .. checkGrad(model, nn.MSECriterion(), input, output))
+
+print('Writing /tmp/graph.dot')
+model:saveDot('/tmp/graph.dot')