added test for GpuImages2Neibs

theano/sandbox/test_neighbours.py

-from numpy import *
+import numpy
 import theano
 from theano import shared, function
 import theano.tensor as T
-from neighbours import images2neibs, neibs2images
+from neighbours import images2neibs, neibs2images, GpuImages2Neibs
+# Skip test if cuda_ndarray is not available.
+from nose.plugins.skip import SkipTest
+import theano.sandbox.cuda as cuda
 
-mode = theano.config.mode
-if mode=="FAST_COMPILE":
-    mode='FAST_RUN'
+if theano.config.mode=='FAST_COMPILE':
+    mode_with_gpu = theano.compile.mode.get_mode('FAST_RUN').including('gpu')
+    mode_without_gpu = theano.compile.mode.get_mode('FAST_RUN').excluding('gpu')
+else:
+    mode_with_gpu = theano.compile.mode.get_default_mode().including('gpu')
+    mode_without_gpu = theano.compile.mode.get_default_mode().excluding('gpu')
 
-def neibs_test():
-    
+def test_neibs():
     shape = (100,40,18,18)
-    images = shared(arange(prod(shape), dtype='float32').reshape(shape))
+    images = shared(numpy.arange(numpy.prod(shape)).reshape(shape))
     neib_shape = T.as_tensor_variable((2,2))#(array((2,2), dtype='float32'))
 
-    f = function([], images2neibs(images, neib_shape), mode=mode)
+    f = function([], images2neibs(images, neib_shape), mode=mode_without_gpu)
 
     #print images.value
     neibs = f()
     #print neibs
-    g = function([], neibs2images(neibs, neib_shape, images.shape), mode=mode)
+    g = function([], neibs2images(neibs, neib_shape, images.shape), mode=mode_without_gpu)
     
     #print g()
-    assert allclose(images.value,g())
+    assert numpy.allclose(images.value,g())
+
+def test_neibs_gpu():
+    if cuda.cuda_available == False:
+       raise SkipTest('Optional package cuda disabled')
+   
+    shape = (100,40,18,18)
+    images = shared(numpy.arange(numpy.prod(shape), dtype='float32').reshape(shape))
+    neib_shape = T.as_tensor_variable((2,2))#(array((2,2), dtype='float32'))
+
+    from theano.sandbox.cuda.basic_ops import gpu_from_host
+
+    f = function([], images2neibs(images,neib_shape),
+                 mode=mode_with_gpu)
+    assert any([isinstance(node.op,GpuImages2Neibs) for node in f.maker.env.toposort()])
+    #print images.value
+    res1=[[[[  0.,   1.,   4.,   5.],
+         [  2.,   3.,   6.,   7.],
+         [  8.,   9.,  12.,  13.],
+         [ 10.,  11.,  14.,  15.],
+         [ 16.,  17.,  20.,  21.],
+         [ 18.,  19.,  22.,  23.],
+         [ 24.,  25.,  28.,  29.],
+         [ 26.,  27.,  30.,  31.],
+         [ 32.,  33.,  36.,  37.],
+         [ 34.,  35.,  38.,  39.],
+         [ 40.,  41.,  44.,  45.],
+         [ 42.,  43.,  46.,  47.],
+         [ 48.,  49.,  52.,  53.],
+         [ 50.,  51.,  54.,  55.],
+         [ 56.,  57.,  60.,  61.],
+         [ 58.,  59.,  62.,  63.]]]]
+    neibs = numpy.asarray(f())
+    numpy.allclose(neibs,res1)
+    #print neibs
+    g = function([], neibs2images(neibs, neib_shape, images.shape), mode=mode_with_gpu)
+    assert any([isinstance(node.op,GpuImages2Neibs) for node in f.maker.env.toposort()])
+    #print numpy.asarray(g())
+    assert numpy.allclose(images.value,g())
 
-neibs_test()
+if __name__ == '__main__':
+    test_neibs_gpu()
+    test_neibs()