From 8616db035c1aeb376e878c48c910fa783d3b0409 Mon Sep 17 00:00:00 2001
From: soumith <soumith@fb.com>
Date: Wed, 24 Dec 2014 16:11:30 -0800
Subject: repro bug

---
 test/test.lua | 75 ++++++++++++++++++++++++++++++++++++++++++++++++++++-------
 1 file changed, 66 insertions(+), 9 deletions(-)

(limited to 'test')

diff --git a/test/test.lua b/test/test.lua
index 03f7c2f..49a941b 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -411,10 +411,34 @@ function cudnntest.Tanh_single()
    mytester:asserteq(rescuda:dim(), 3, 'error in dimension')
    mytester:asserteq(resgrad:dim(), 3, 'error in dimension')
    local error = rescuda:float() - groundtruth:float()
-   mytester:assertlt(error:abs():max(), precision_forward,
+   local errmax = error:abs():max()
+   if (errmax ~= errmax) then
+      local state = {}
+      state.input = input
+      state.gradOutput = gradOutput
+      state.rescuda = rescuda
+      state.resgrad = resgrad
+      state.groundtruth = groundtruth
+      state.groundgrad = groundgrad
+      print(#input)
+      torch.save('badTanh.t7', state)
+   end
+   mytester:assertlt(errmax, precision_forward,
                      'error on state (forward) ')
    error = resgrad:float() - groundgrad:float()
-   mytester:assertlt(error:abs():max(), precision_backward,
+   errmax = error:abs():max()
+   if (errmax ~= errmax) then
+      local state = {}
+      state.input = input
+      state.gradOutput = gradOutput
+      state.rescuda = rescuda
+      state.resgrad = resgrad
+      state.groundtruth = groundtruth
+      state.groundgrad = groundgrad
+      print(#input)
+      torch.save('badTanh.t7', state)
+   end
+   mytester:assertlt(errmax, precision_backward,
                      'error on state (backward) ')
 end
 
@@ -478,10 +502,27 @@ function cudnntest.Sigmoid_single()
    mytester:asserteq(rescuda:dim(), 3, 'error in dimension')
    mytester:asserteq(resgrad:dim(), 3, 'error in dimension')
    local error = rescuda:float() - groundtruth:float()
-   mytester:assertlt(error:abs():max(), precision_forward,
+   local errmax = error:abs():max()
+   if (errmax ~= errmax) then
+      print(#input)
+   end
+   mytester:assertlt(errmax, precision_forward,
                      'error on state (forward) ')
    error = resgrad:float() - groundgrad:float()
-   mytester:assertlt(error:abs():max(), precision_backward,
+   errmax = error:abs():max()
+   if (errmax ~= errmax) then
+      local state = {}
+      state.input = input
+      state.gradOutput = gradOutput
+      state.rescuda = rescuda
+      state.resgrad = resgrad
+      state.groundtruth = groundtruth
+      state.groundgrad = groundgrad
+      print(#input)
+      torch.save('badSoftMax.t7', state)
+      print(#input)
+   end
+   mytester:assertlt(errmax, precision_backward,
                      'error on state (backward) ')
 end
 
@@ -544,13 +585,29 @@ function cudnntest.SoftMax_single()
    cutorch.synchronize()
    mytester:asserteq(rescuda:dim(), 3, 'error in dimension')
    mytester:asserteq(resgrad:dim(), 3, 'error in dimension')
-
    local error = rescuda:float() - groundtruth:float()
-   mytester:assertlt(error:abs():max(),
-                     precision_forward, 'error on state (forward) ')
+   local errmax = error:abs():max()
+   if (errmax ~= errmax) then
+      local state = {}
+      state.input = input
+      state.gradOutput = gradOutput
+      state.rescuda = rescuda
+      state.resgrad = resgrad
+      state.groundtruth = groundtruth
+      state.groundgrad = groundgrad
+      print(#input)
+      torch.save('badSoftMax.t7', state)
+      print(#input)
+   end
+   mytester:assertlt(errmax, precision_forward,
+                     'error on state (forward) ')
    error = resgrad:float() - groundgrad:float()
-   mytester:assertlt(error:abs():max(),
-                     precision_backward, 'error on state (backward) ')
+   errmax = error:abs():max()
+   if (errmax ~= errmax) then
+      print(#input)
+   end
+   mytester:assertlt(errmax, precision_backward,
+                     'error on state (backward) ')
 end
 
 function cudnntest.SoftMax_batch()
-- 
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