Added SpatialDropout + doc + test.

1 files changed, 29 insertions, 1 deletions

diff --git a/test.lua b/test.lua
index a15cd61..27a1747 100644
--- a/test.lua
+++ b/test.lua
@@ -37,7 +37,6 @@ for test_name, component in pairs(tostringTestModules) do
     end
 end
 
-
 function nntest.Add()
    local inj_vals = {math.random(3,5), 1}  -- Also test the inj = 1 spatial case
    local ini = math.random(3,5)
@@ -172,6 +171,35 @@ function nntest.Dropout()
    mytester:assert(math.abs(gradInput:mean() - (1-p)) < 0.05, 'dropout gradInput')
 end
 
+function nntest.SpatialDropout()
+   local p = 0.2 --prob of dropiing out a neuron
+   local w = math.random(1,5)
+   local h = math.random(1,5)
+   local nfeats = 1000
+   local input = torch.Tensor(nfeats, w, h):fill(1)
+   local module = nn.SpatialDropout(p)
+   module.train = true
+   local output = module:forward(input)
+   mytester:assert(math.abs(output:mean() - (1-p)) < 0.05, 'dropout output')
+   local gradInput = module:backward(input, input)
+   mytester:assert(math.abs(gradInput:mean() - (1-p)) < 0.05, 'dropout gradInput')
+end
+
+function nntest.SpatialDropoutBatch()
+   local p = 0.2 --prob of dropiing out a neuron
+   local bsz = math.random(1,5)
+   local w = math.random(1,5)
+   local h = math.random(1,5)
+   local nfeats = 1000
+   local input = torch.Tensor(bsz, nfeats, w, h):fill(1)
+   local module = nn.SpatialDropout(p)
+   module.train = true
+   local output = module:forward(input)
+   mytester:assert(math.abs(output:mean() - (1-p)) < 0.05, 'dropout output')
+   local gradInput = module:backward(input, input)
+   mytester:assert(math.abs(gradInput:mean() - (1-p)) < 0.05, 'dropout gradInput')
+end
+
 function nntest.ReLU()
    local input = torch.randn(3,4)
    local gradOutput = torch.randn(3,4)