Use Height x Width notation in hello world examples

examples/hello-world.lua

@@ -11,15 +11,15 @@ tensorType = scn.cutorch and 'torch.CudaTensor' or 'torch.FloatTensor'
 
 model = scn.Sequential()
   :add(scn.SparseVggNet(2,1,{ --dimension 2, 1 input plane
-                          {'C', 8}, -- 3x3 VSC convolution, 8 output planes, batchnorm, ReLU
-                          {'C', 8}, -- and another
-                          {'MP', 3, 2}, --max pooling, size 3, stride 2
-                          {'C', 16}, -- etc
-                          {'C', 16},
-                          {'MP', 3, 2},
-                          {'C', 24},
-                          {'C', 24},
-                          {'MP', 3, 2}}))
+			  {'C', 8}, -- 3x3 VSC convolution, 8 output planes, batchnorm, ReLU
+			  {'C', 8}, -- and another
+			  {'MP', 3, 2}, --max pooling, size 3, stride 2
+			  {'C', 16}, -- etc
+			  {'C', 16},
+			  {'MP', 3, 2},
+			  {'C', 24},
+			  {'C', 24},
+			  {'MP', 3, 2}}))
   :add(scn.Convolution(2,24,32,3,1,false)) --an SC convolution on top
   :add(scn.BatchNormReLU(32))
   :add(scn.SparseToDense(2))
@@ -47,7 +47,7 @@ input:addSample()
 for y,line in ipairs(msg) do
   for x = 1,string.len(line) do
     if string.sub(line,x,x) == 'O' then
-      local location = torch.LongTensor{x,y}
+      local location = torch.LongTensor{y, x}
       local featureVector = torch.FloatTensor{1}
       input:setLocation(location,featureVector,0)
     end
@@ -61,7 +61,7 @@ local featureVectors = {}
 for y,line in ipairs(msg) do
   for x = 1,string.len(line) do
     if string.sub(line,x,x) == 'O' then
-      table.insert(locations, {x,y})
+      table.insert(locations, {y, x})
       table.insert(featureVectors, {1})
     end
   end

examples/hello-world.py

@@ -12,9 +12,9 @@ use_gpu = torch.cuda.is_available()
 
 model = scn.Sequential().add(
     scn.SparseVggNet(2, 1,
-                     [['C',  8], ['C',  8], ['MP', 3, 2],
-                      ['C', 16], ['C', 16], ['MP', 3, 2],
-                      ['C', 24], ['C', 24], ['MP', 3, 2]])
+		     [['C',  8], ['C',  8], ['MP', 3, 2],
+		      ['C', 16], ['C', 16], ['MP', 3, 2],
+		      ['C', 24], ['C', 24], ['MP', 3, 2]])
 ).add(
     scn.ValidConvolution(2, 24, 32, 3, False)
 ).add(
@@ -40,10 +40,10 @@ msg = [
 input.addSample()
 for y, line in enumerate(msg):
     for x, c in enumerate(line):
-        if c == 'X':
-            location = torch.LongTensor([x, y])
-            featureVector = torch.FloatTensor([1])
-            input.setLocation(location, featureVector, 0)
+	if c == 'X':
+	    location = torch.LongTensor([y, x])
+	    featureVector = torch.FloatTensor([1])
+	    input.setLocation(location, featureVector, 0)
 
 #Add a sample using setLocations
 input.addSample()
@@ -51,9 +51,9 @@ locations = []
 features = []
 for y, line in enumerate(msg):
     for x, c in enumerate(line):
-        if c == 'X':
-            locations.append([x,y])
-            features.append([1])
+	if c == 'X':
+	    locations.append([y, x])
+	    features.append([1])
 locations = torch.LongTensor(locations)
 features = torch.FloatTensor(features)
 input.setLocations(locations, features, 0)