Add support for torch.HalfTensor (#874)

* Add support for torch.HalfTensor.

* Improvements/Simplifications for torch.HalfTensor.

Improvements/Simplifications:
1) Defines half type as TH_Half, so as to not conflict with cutorch
version.  Previously, these were defined as the same "half" type and
required proper ordering of includes to ensure type was only defined
once, which would have affected all downstream projects.
2) No longer generates math functions that are not actually defined
on torch.HalfTensor, e.g. maskedFill, map, etc.
3) Adds tests for all available torch.HalfTensor functions
4) Allows compiling without TH_GENERIC_USE_HALF (so if there's a
problem can just unset that in CMakeLists rather than backing out)
5) Some simplifications: removes a new copy optimization and
some TH_HALF literal definitions

Limitations:
Because match functions are not defined, some "non-math" operators
on torch.HalfTensor give an error message, e.g. __index__/__newindex__
with a ByteTensor apply a mask, but masks aren't implemented.  These
limitations aren't always obvious, (e.g. for documentation purposes),
but they should always give an error message.

* Rename TH_HALF to THHalf.

1 files changed, 15 insertions, 3 deletions

diff --git a/Tensor.lua b/Tensor.lua
index b4b3e95..36307bd 100644
--- a/Tensor.lua
+++ b/Tensor.lua
@@ -5,14 +5,14 @@ local Storage = {}
 local Tensor = {}
 
 -- types
-local types = {'Byte', 'Char', 'Short', 'Int', 'Long', 'Float', 'Double'}
+local types = {'Byte', 'Char', 'Short', 'Int', 'Long', 'Float', 'Half', 'Double'}
 
 -- Lua 5.2 compatibility
 local log10 = math.log10 or function(x) return math.log(x, 10) end
 
 -- tostring() functions for Tensor and Storage
 local function Storage__printformat(self)
-   if self:size() == 0 then 
+   if self:size() == 0 then
      return "", nil, 0
    end
    local intMode = true
@@ -277,6 +277,10 @@ function Tensor.double(self)
    return self:type('torch.DoubleTensor')
 end
 
+function Tensor.half(self)
+   return self:type('torch.HalfTensor')
+end
+
 function Tensor.real(self)
    return self:type(torch.getdefaulttensortype())
 end
@@ -556,6 +560,14 @@ torch.permute = Tensor.permute
 for _,type in ipairs(types) do
    local metatable = torch.getmetatable('torch.' .. type .. 'Tensor')
    for funcname, func in pairs(Tensor) do
-      rawset(metatable, funcname, func)
+      if funcname ~= 'totable' or type ~='Half' or torch.hashalfmath() then
+         rawset(metatable, funcname, func)
+      else
+         local function Tensor__totable(self)
+            local host_tensor = self:float()
+            return self:float():totable()
+         end
+         rawset(torch.getmetatable('torch.HalfTensor'), 'totable', Tensor__totable)
+      end
    end
 end