Added one more test for SparseLinear

2 files changed, 68 insertions, 0 deletions

diff --git a/SparseJacobian.lua b/SparseJacobian.lua
index 3dd489d..b778e67 100644
--- a/SparseJacobian.lua
+++ b/SparseJacobian.lua
@@ -217,3 +217,61 @@ function nn.SparseJacobian.testIO(module,input, minval, maxval)
    local errb = bo - bo2
    return errf:abs():max(), errb:abs():max()
 end
+
+function nn.SparseJacobian.testAllUpdate(module, input, weight, gradWeight)
+   local gradOutput
+   local lr = torch.uniform(0.1, 1)
+   local errors = {}
+
+   -- accGradParameters
+   local maccgp = module:clone()
+   local weightc = maccgp[weight]:clone()
+   maccgp:forward(input)
+   gradOutput = torch.rand(maccgp.output:size())
+   maccgp:zeroGradParameters()
+   maccgp:updateGradInput(input, gradOutput)
+   maccgp:accGradParameters(input, gradOutput)
+   maccgp:updateParameters(lr)
+   errors["accGradParameters"] = (weightc-maccgp[gradWeight]*lr-maccgp[weight]):norm()
+   
+   -- accUpdateGradParameters
+   local maccugp = module:clone()
+   maccugp:forward(input)
+   maccugp:updateGradInput(input, gradOutput)
+   maccugp:accUpdateGradParameters(input, gradOutput, lr)
+   errors["accUpdateGradParameters"] = (maccugp[weight]-maccgp[weight]):norm()
+
+   -- shared, accGradParameters
+   local macsh1 = module:clone()
+   local macsh2 = module:clone()
+   macsh2:share(macsh1, weight)
+   macsh1:forward(input)
+   macsh2:forward(input)
+   macsh1:zeroGradParameters()
+   macsh2:zeroGradParameters()
+   macsh1:updateGradInput(input, gradOutput)
+   macsh2:updateGradInput(input, gradOutput)
+   macsh1:accGradParameters(input, gradOutput)
+   macsh2:accGradParameters(input, gradOutput)
+   macsh1:updateParameters(lr)
+   macsh2:updateParameters(lr)
+   local err = (weightc-maccgp[gradWeight]*(lr*2)-macsh1[weight]):norm()
+   err = err + (weightc-maccgp[gradWeight]*(lr*2)-macsh2[weight]):norm()
+   errors["accGradParameters [shared]"] = err
+   
+   -- shared, accUpdateGradParameters
+   local macshu1 = module:clone()
+   local macshu2 = module:clone()
+   macshu2:share(macshu1, weight)
+   macshu1:forward(input)
+   macshu2:forward(input)
+   macshu1:updateGradInput(input, gradOutput)
+   macshu2:updateGradInput(input, gradOutput)
+   macshu1:accUpdateGradParameters(input, gradOutput, lr)
+   macshu2:accUpdateGradParameters(input, gradOutput, lr)
+   local err = (weightc-maccgp[gradWeight]*(lr*2)-macshu1[weight]):norm()
+   err = err + (weightc-maccgp[gradWeight]*(lr*2)-macshu2[weight]):norm()
+   errors["accUpdateGradParameters [shared]"] = err
+
+   return errors
+end
diff --git a/test/test.lua b/test/test.lua
index eb6dede..df80616 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -350,6 +350,16 @@ function nntest.SparseLinear()
 
    local err = sjac.testJacobianUpdateParameters(module, input, module.bias)
    mytester:assertlt(err,precision, 'error on bias [direct update] ')
+   
+   for t,err in pairs(sjac.testAllUpdate(module, input, 'weight', 'gradWeight')) do
+      mytester:assertlt(err, precision, string.format(
+                         'error on weight [%s]', t))
+   end
+
+   for t,err in pairs(sjac.testAllUpdate(module, input, 'bias', 'gradBias')) do
+      mytester:assertlt(err, precision, string.format(
+                         'error on bias [%s]', t))
+   end
 
    local ferr, berr = sjac.testIO(module, input)
    mytester:asserteq(0, ferr, torch.typename(module) .. ' - i/o forward err ')