Fix TemporalConvolution output size

Issue seen in updateOutput() when batch size is decreasing (e.g. 256->128):
```
.../torch/install/share/lua/5.1/torch/Tensor.lua:462: Wrong size for view. Input size: 66060288. Output size: 128x256x1008x1
stack traceback:
	[C]: in function 'error'
	.../torch/install/share/lua/5.1/torch/Tensor.lua:462: in function 'view'
	...orch/install/share/lua/5.1/cudnn/TemporalConvolution.lua:62: in function <...orch/install/share/lua/5.1/cudnn/TemporalConvolution.lua:54>

```

See new test cudnntest.TemporalConvolution_reduceBatchSize() for a repro.

Calling a tensor's set() method without extra parameters but the requested storage causes the tensor to see a 1-D view of the full storage (not the associated tensor). For example:
```
th> x=torch.Tensor(10)
                                                                      [0.0001s]
th> y=x:resize(5)
                                                                      [0.0001s]
th> torch.Tensor():set(y:storage()):size()
 10
[torch.LongStorage of size 1]

                                                                      [0.0002s]

```

Proposed fix is to specify the desired view through the optional parameters of the set() method.

1 files changed, 23 insertions, 0 deletions

diff --git a/test/test.lua b/test/test.lua
index 55171c7..fd7693a 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -448,6 +448,29 @@ function cudnntest.TemporalConvolution_single()
    mytester:assertlt(berror:abs():max(), precision_backward, 'error on bias (backward) ')
 end
 
+function cudnntest.TemporalConvolution_reduceBatchSize()
+   local inputFrameSize = math.random(1,64)
+   local outputFrameSize = math.random(1,64)
+   local ki = math.random(1,15)
+   local si = math.random(1,ki)
+   local outi = math.random(1,15)
+   local ini = (outi-1)*si+ki
+   local batchSize = 128
+   local smallerBatchSize = batchSize/2
+
+   local input
+   input = torch.randn(batchSize,ini,inputFrameSize):cuda()
+   local conv = cudnn.TemporalConvolution(inputFrameSize,outputFrameSize,ki,si):cuda()
+   local o1 = conv:updateOutput(input)
+   mytester:asserteq(o1:size(1), batchSize, 'batch size didn\'t match')
+
+   input = torch.randn(smallerBatchSize,ini,inputFrameSize):cuda()
+   local o2 = conv:updateOutput(input)
+   mytester:asserteq(o2:size(1), smallerBatchSize, 'batch size didn\'t match')
+   -- do this again to check it doesn't crash
+   local o2 = conv:updateOutput(input)
+   mytester:asserteq(o2:size(1), smallerBatchSize, 'batch size didn\'t match')
+end
 
 
 function cudnntest.VolumetricConvolution_forward_single()