unit test for 1D LookupTable

1 files changed, 54 insertions, 0 deletions

diff --git a/test/test.lua b/test/test.lua
index b2b5f92..91b38e8 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -1646,6 +1646,60 @@ function nntest.PairwiseDistance()
   end
 end
 
+function nntest.LookupTable()
+   local totalIndex = math.random(10,100)
+   local nIndex = math.random(5,7)
+   local entry_size = math.random(5,7)
+   local input = torch.Tensor(nIndex):zero()
+   local module = nn.LookupTable(totalIndex, entry_size)
+   local minval = 1
+   local maxval = totalIndex
+
+   -- 1D
+   local err = jac.testJacobianParameters(module, input, module.weight, module.gradWeight, minval, maxval)
+   mytester:assertlt(err,precision, 'error on weight ')
+
+   local err = jac.testJacobianUpdateParameters(module, input, module.weight, minval, maxval)
+   mytester:assertlt(err,precision, 'error on weight [direct update] ')
+   
+   module.gradWeight:zero()
+   for t,err in pairs(jac.testAllUpdate(module, input, 'weight', 'gradWeight')) do
+      mytester:assertlt(err, precision, string.format(
+                         'error on weight [%s]', t))
+   end
+
+   -- 2D
+   local nframe = math.random(50,70)
+   local input = torch.Tensor(nframe, nIndex):zero()
+
+   local err = jac.testJacobianParameters(module, input, module.weight, module.gradWeight)
+   mytester:assertlt(err,precision, 'error on weight ')
+
+   local err = jac.testJacobianParameters(module, input, module.bias, module.gradBias)
+   mytester:assertlt(err,precision, 'error on weight ')
+
+   local err = jac.testJacobianUpdateParameters(module, input, module.weight)
+   mytester:assertlt(err,precision, 'error on weight [direct update] ')
+
+   local err = jac.testJacobianUpdateParameters(module, input, module.bias)
+   mytester:assertlt(err,precision, 'error on bias [direct update] ')
+
+   for t,err in pairs(jac.testAllUpdate(module, input, 'weight', 'gradWeight')) do
+      mytester:assertlt(err, precision, string.format(
+                         'error on weight [%s]', t))
+   end
+
+   for t,err in pairs(jac.testAllUpdate(module, input, 'bias', 'gradBias')) do
+      mytester:assertlt(err, precision, string.format(
+                         'error on bias [%s]', t))
+   end
+
+   -- IO
+   local ferr,berr = jac.testIO(module,input)
+   mytester:asserteq(ferr, 0, torch.typename(module) .. ' - i/o forward err ')
+   mytester:asserteq(berr, 0, torch.typename(module) .. ' - i/o backward err ')
+end
+
 mytester:add(nntest)
 
 if not nn then