Merge pull request #933 from torch/maxminfix

fixing Max and Min for new cutorch types

3 files changed, 9 insertions, 36 deletions

diff --git a/Max.lua b/Max.lua
index 691fe9d..1392d8a 100644
--- a/Max.lua
+++ b/Max.lua
@@ -21,7 +21,7 @@ end
 function Max:_lazyInit()
    self._output = self._output or self.output.new()
    self._indices = self._indices or
-      (torch.type(self.output) == 'torch.CudaTensor' and torch.CudaTensor() or torch.LongTensor())
+      (torch.type(self.output) == 'torch.CudaTensor' and torch.CudaLongTensor() or torch.LongTensor())
 end
 
 function Max:updateOutput(input)
@@ -50,18 +50,9 @@ function Max:updateGradInput(input, gradOutput)
 end
 
 function Max:type(type, tensorCache)
-  -- torch.max expects a LongTensor as indices, whereas cutorch.max expects a CudaTensor.
-  if type == 'torch.CudaTensor' then
+    self._indices = nil
     parent.type(self, type, tensorCache)
-  else
-    -- self._indices must be a LongTensor. Setting it to nil temporarily avoids
-    -- unnecessary memory allocations.
-    local indices
-    indices, self._indices = self._indices, nil
-    parent.type(self, type, tensorCache)
-    self._indices = indices and indices:long() or nil
-  end
-  return self
+    return self
 end
 
 function Max:clearState()
diff --git a/Min.lua b/Min.lua
index f1d2b45..dc07cf9 100644
--- a/Min.lua
+++ b/Min.lua
@@ -21,7 +21,7 @@ end
 function Min:_lazyInit()
    self._output = self._output or self.output.new()
    self._indices = self._indices or
-      (torch.type(self.output) == 'torch.CudaTensor' and torch.CudaTensor() or torch.LongTensor())
+      (torch.type(self.output) == 'torch.CudaTensor' and torch.CudaLongTensor() or torch.LongTensor())
 end
 
 function Min:updateOutput(input)
@@ -50,18 +50,9 @@ function Min:updateGradInput(input, gradOutput)
 end
 
 function Min:type(type, tensorCache)
-  -- torch.min expects a LongTensor as indices, whereas cutorch.max expects a CudaTensor.
-  if type == 'torch.CudaTensor' then
+    self._indices = nil
     parent.type(self, type, tensorCache)
-  else
-    -- self._indices must be a LongTensor. Setting it to nil temporarily avoids
-    -- unnecessary memory allocations.
-    local indices
-    indices, self._indices = self._indices, nil
-    parent.type(self, type, tensorCache)
-    self._indices = indices and indices:long() or nil
-  end
-  return self
+    return self
 end
 
 function Min:clearState()
diff --git a/Normalize.lua b/Normalize.lua
index 24c1d07..5cd4857 100644
--- a/Normalize.lua
+++ b/Normalize.lua
@@ -25,7 +25,7 @@ function Normalize:updateOutput(input)
     -- specialization for the infinity norm
     self._indices = self._indices or
       (torch.type(self.output) == 'torch.CudaTensor' and
-       torch.CudaTensor() or torch.LongTensor())
+       torch.CudaLongTensor() or torch.LongTensor())
 
     self.buffer:abs(input)
     torch.max(self.norm, self._indices, self.buffer, 2)
@@ -127,18 +127,9 @@ function Normalize:__tostring__()
 end
 
 function Normalize:type(type, tensorCache)
-  -- torch.max expects a LongTensor as indices, whereas cutorch.max expects a CudaTensor.
-  if type == 'torch.CudaTensor' then
+    self._indices = nil
     parent.type(self, type, tensorCache)
-  else
-    -- self._indices must be a LongTensor. Setting it to nil temporarily avoids
-    -- unnecessary memory allocations.
-    local indices
-    indices, self._indices = self._indices, nil
-    parent.type(self, type, tensorCache)
-    self._indices = indices and indices:long() or nil
-  end
-  return self
+    return self
 end
 
 function Normalize:clearState()