Merge pull request #119 from nicholas-leonard/weightedeuclidean

WeightedEuclidean batch mode

1 files changed, 36 insertions, 1 deletions

diff --git a/test.lua b/test.lua
index 29de8bc..56298e0 100644
--- a/test.lua
+++ b/test.lua
@@ -477,7 +477,7 @@ function nntest.WeightedEuclidean()
    local inj = math.random(13,5)
    local input = torch.Tensor(ini):zero()
    local module = nn.WeightedEuclidean(ini,inj)
-
+   
    local err = jac.testJacobian(module,input)
    mytester:assertlt(err,precision, 'error on state ')
 
@@ -490,6 +490,41 @@ function nntest.WeightedEuclidean()
    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 ')
+   
+   -- test batch
+   local bs = math.random(3,5)
+   input:uniform(0,1)
+   local output = module:forward(input):clone()
+   module:zeroGradParameters()
+   local gradInput = module:backward(input, output):clone()
+   local params, gradParams = module:parameters()
+   for i=1,#params do
+      params[i] = params[i]:clone()
+   end
+   local input2 = input:view(1, -1):repeatTensor(bs, 1)
+   local output2 = module:forward(input2)
+   module:zeroGradParameters()
+   local gradInput2 = module:backward(input2, output2, 1/bs)
+   local params2, gradParams2 = module:parameters()
+   mytester:assertTensorEq(output2[bs-1], output, 0.000001, "error in batch updateOutput")
+   mytester:assertTensorEq(gradInput2[bs-1], gradInput, 0.000001, "error in batch updateGradInput")
+   mytester:assertTensorEq(gradParams[1], gradParams2[1], 0.000001, "error in batch accGradParameters (gradTemplates)")
+   mytester:assertTensorEq(gradParams[2], gradParams2[2], 0.000001, "error in batch accGradParameters (gradDiagCov)")
+   
+   input:zero()
+   module:zeroGradParameters()
+   local err = jac.testJacobian(module,input)
+   mytester:assertlt(err,precision, 'error on state ')
+
+   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 bias ')
+
+   local ferr,berr = jac.testIO(module,input2)
+   mytester:asserteq(ferr, 0, torch.typename(module) .. ' - i/o forward err ')
+   mytester:asserteq(berr, 0, torch.typename(module) .. ' - i/o backward err ')
 end
 
 local function criterionJacobianTest1D(cri, input, target)