added speed test for the new generalized collapse of dimensions.

theano/sandbox/cuda/tests/test_basic_ops.py

@@ -124,7 +124,7 @@ def test_elemwise4():
 
 
 def speed_elemwise_collapse():
-    """ used to time if the collapse of ccontiguous row are usefull """
+    """ used to time if the collapse of ccontiguous dims are usefull """
     
     shape = (30,40,50,600)
     a = cuda_ndarray.CudaNdarray(numpy.asarray(numpy.random.rand(*shape),dtype='float32'))
@@ -147,6 +147,30 @@ def speed_elemwise_collapse():
        f(v)
     t2=time.time()
 
+def speed_elemwise_collapse2():
+    """ used to test the speed up of the generalised collapse of ccontiguous dims"""
+    
+    shape = (30,40,50,600)
+    a = cuda_ndarray.CudaNdarray(numpy.asarray(numpy.random.rand(*shape),dtype='float32'))
+    a = numpy.asarray(numpy.random.rand(*shape),dtype='float32')
+    a2 = tcn.shared_constructor(a, 'a')
+    a3 = a2[:,:,:,::2]
+    b = tcn.CudaNdarrayType((False, False, False, False))()
+    c = a3+b * tensor.exp(1 + b**a3)
+    f = pfunc([b], [c])
+
+
+    v = numpy.asarray(numpy.random.rand(*shape),dtype='float32')
+    v = v[:,:,:,::2]
+    v=cuda_ndarray.CudaNdarray(v)
+    for id,n in enumerate(f.maker.env.toposort()):
+        print id, n
+    t1=time.time()
+    for i in range(100):
+       #let debugmode catch errors
+       f(v)
+    t2=time.time()
+
 def test_elemwise_collapse():
     """ used to test if the case where all inputs are broadcast """