Add a keepdim parameter for reduction functions over a single dimension.

By default, this parameter is False -- a backwards incompatible change, but
one that follows numpy semantics, e.g. numpy.sum (numpy names the parameter
"keepdims" since you can pass multiple dims to reduction functions).

The old behavior seems desired for normalization type operations
where the tensor will immediately be expanded out again, e.g.:
probs.sum(1).expand_as(probs)
which no longer works because the dimension to expand is missing.
This can be fixed by simply passing True as "keepdim" argument
to the reduction operation, e.g:
probs.sum(1, keepdim=True).expand_as(probs)

2 files changed, 3 insertions, 3 deletions

diff --git a/lib/THNN/generic/SparseLinear.c b/lib/THNN/generic/SparseLinear.c
index d9cec8c..1cf7122 100644
--- a/lib/THNN/generic/SparseLinear.c
+++ b/lib/THNN/generic/SparseLinear.c
@@ -234,7 +234,7 @@ void THNN_(SparseLinear_accGradParameters)(
 
   // gradBias += gradOutput
   THTensor* buf = THTensor_(new)();
-  THTensor_(sum)(buf, gradOutput, 0);
+  THTensor_(sum)(buf, gradOutput, 0, 1);
   THTensor_(cadd)(gradBias, gradBias, scale, buf);
   THTensor_(free)(buf);
   THLongTensor_free(csc);
diff --git a/lib/THNN/generic/TemporalSubSampling.c b/lib/THNN/generic/TemporalSubSampling.c
index 6b788df..68f35e2 100644
--- a/lib/THNN/generic/TemporalSubSampling.c
+++ b/lib/THNN/generic/TemporalSubSampling.c
@@ -70,7 +70,7 @@ void THNN_(TemporalSubSampling_updateOutput)(
   {
     THTensor_(narrow)(inputWindow, input, 0, k*dW, kW);
     THTensor_(select)(outputFrame, output, 0, k);
-    THTensor_(sum)(outputFrame, inputWindow, 0);
+    THTensor_(sum)(outputFrame, inputWindow, 0, 1);
     THTensor_(cmul)(outputFrame, outputFrame, weight);
     THTensor_(cadd)(outputFrame, outputFrame, 1, bias);
   }
@@ -143,7 +143,7 @@ void THNN_(TemporalSubSampling_accGradParameters)(
   {
     THTensor_(narrow)(inputWindow, input, 0, k*dW, kW);
     THTensor_(select)(gradOutputFrame, gradOutput, 0, k);
-    THTensor_(sum)(buffer, inputWindow, 0);
+    THTensor_(sum)(buffer, inputWindow, 0, 1);
     THTensor_(addcmul)(gradWeight, gradWeight, scale, buffer, gradOutputFrame);
     THTensor_(cadd)(gradBias, gradBias, scale, gradOutputFrame);
   }