Added Divisive Normalization module.

1 files changed, 32 insertions, 0 deletions

diff --git a/test/test.lua b/test/test.lua
index d67165f..31a6049 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -556,6 +556,38 @@ function nntest.SpatialSubtractiveNormalization_1dkernel()
    mytester:asserteq(berr, 0, torch.typename(module) .. ' - i/o backward err ')
 end
 
+function nntest.SpatialDivisiveNormalization_2dkernel()
+   local inputSize = math.random(11,20)
+   local kersize = 9
+   local nbfeatures = math.random(5,10)
+   local kernel = torch.Tensor(kersize,kersize):fill(1)
+   local module = nn.SpatialDivisiveNormalization(nbfeatures,kernel)
+   local input = torch.rand(nbfeatures,inputSize,inputSize)
+
+   local err = jac.testJacobian(module,input)
+   mytester:assertlt(err,precision, 'error on state ')
+
+   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
+
+function nntest.SpatialDivisiveNormalization_1dkernel()
+   local inputSize = math.random(11,20)
+   local kersize = 9
+   local nbfeatures = math.random(5,10)
+   local kernel = torch.Tensor(kersize):fill(1)
+   local module = nn.SpatialDivisiveNormalization(nbfeatures,kernel)
+   local input = torch.rand(nbfeatures,inputSize,inputSize)
+
+   local err = jac.testJacobian(module,input)
+   mytester:assertlt(err,precision, 'error on state ')
+
+   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
+
 function nntest.SpatialConvolution()
    local from = math.random(1,10)
    local to = math.random(1,10)