Add support for negative indices in nn.SplitTable

This module can now be used when the total number of dimensions is unknown.

SplitTable.lua

@@ -6,13 +6,21 @@ function SplitTable:__init(dimension, nInputDims)
    self.nInputDims = nInputDims
 end
 
-function SplitTable:updateOutput(input)
+function SplitTable:_getPositiveDimension(input)
    local dimension = self.dimension
-   if self.nInputDims and input:dim()==(self.nInputDims+1) then
-       dimension = dimension + 1
+   if dimension < 0 then
+      dimension = input:dim() + dimension + 1
+   elseif self.nInputDims and input:dim()==(self.nInputDims+1) then
+      dimension = dimension + 1
    end
-   local currentOutput= {}
+   return dimension
+end
+
+function SplitTable:updateOutput(input)
+   local dimension = self:_getPositiveDimension(input)
    local slices = input:size(dimension)
+
+   local currentOutput= {}
    for i=1,slices do
       currentOutput[#currentOutput+1] = input:select(dimension,i)
    end
@@ -21,10 +29,7 @@ function SplitTable:updateOutput(input)
 end 
 
 function SplitTable:updateGradInput(input, gradOutput)
-   local dimension = self.dimension
-   if self.nInputDims and input:dim()==(self.nInputDims+1) then
-      dimension = dimension + 1
-   end
+   local dimension = self:_getPositiveDimension(input)
    local slices = input:size(dimension)
    self.gradInput:resizeAs(input)
 

doc/table.md

@@ -315,6 +315,53 @@ gives the output:
 [torch.DoubleTensor of dimension 3]
 ```
 
+The module also supports indexing from the end using negative dimensions. This allows to use this module when the number of dimensions of the input is unknown.
+
+### Example
+
+```lua
+m = nn.SplitTable(-2)
+out = m:forward(torch.randn(3, 2))
+for i, k in ipairs(out) do print(i, k) end
+out = m:forward(torch.randn(1, 3, 2))
+for i, k in ipairs(out) do print(i, k) end
+```
+
+gives the output:
+
+```
+1
+ 0.1420
+-0.5698
+[torch.DoubleTensor of size 2]
+
+2
+ 0.1663
+ 0.1197
+[torch.DoubleTensor of size 2]
+
+3
+ 0.4198
+-1.1394
+[torch.DoubleTensor of size 2]
+
+
+1
+-2.4941
+-1.4541
+[torch.DoubleTensor of size 1x2]
+
+2
+ 0.4594
+ 1.1946
+[torch.DoubleTensor of size 1x2]
+
+3
+-2.3322
+-0.7383
+[torch.DoubleTensor of size 1x2]
+```
+
 ### A more complicated example
 
 ```lua

test.lua

@@ -2928,6 +2928,13 @@ function nntest.SplitTable()
       module = nn.SplitTable(d, 2)
       mytester:asserteq(#module:forward(input), input:size(d+1), "dimension " .. d)
    end
+
+   -- Negative indices
+   local module = nn.SplitTable(-3)
+   local input = torch.randn(3,4,5)
+   mytester:asserteq(#module:forward(input), 3, "negative index")
+   local input = torch.randn(2,3,4,5)
+   mytester:asserteq(#module:forward(input), 3, "negative index (minibatch)")
 end
 
 function nntest.SelectTable()