Add test for Rebroadcast on GpuArrayVariables

theano/sandbox/gpuarray/tests/test_opt.py

 import numpy
 
 import theano
+from theano import tensor
 from theano.tests import unittest_tools as utt
+import theano.sandbox.gpuarray
+from theano.sandbox.gpuarray.type import GpuArrayType
 from theano.sandbox.gpuarray.basic_ops import GpuAlloc, GpuReshape, gpu_alloc
 from theano.sandbox.gpuarray.elemwise import GpuCAReduceCuda
-import theano.sandbox.gpuarray
+from theano.sandbox.gpuarray.tests.test_basic_ops import (
+    rand_gpuarray, mode_with_gpu, mode_without_gpu
+    )
 from theano.tests.unittest_tools import SkipTest
 
-if theano.sandbox.gpuarray.pygpu is None:
-    raise SkipTest("pygpu not installed")
-
-import theano.sandbox.cuda as cuda_ndarray
-if cuda_ndarray.cuda_available and not theano.sandbox.gpuarray.pygpu_activated:
-    if not cuda_ndarray.use.device_number:
-        cuda_ndarray.use('gpu')
-    theano.sandbox.gpuarray.init_dev('cuda')
-
-if not theano.sandbox.gpuarray.pygpu_activated:
-    raise SkipTest("pygpu disabled")
-
-if theano.config.mode == 'FAST_COMPILE':
-    mode_with_gpu = theano.compile.mode.get_mode('FAST_RUN').including('gpuarray').excluding('gpu')
-    mode_without_gpu = theano.compile.mode.get_mode('FAST_RUN').excluding('gpuarray')
-else:
-    mode_with_gpu = theano.compile.mode.get_default_mode().including('gpuarray').excluding('gpu')
-    mode_without_gpu = theano.compile.mode.get_default_mode().excluding('gpuarray')
-
-
 def test_flatten():
     m = theano.tensor.fmatrix()
     f = theano.function([m], m.flatten(), mode=mode_with_gpu)
@@ -104,3 +89,20 @@ def test_local_gpualloc_memset_0():
     assert isinstance(topo[0].op, GpuAlloc)
     assert not topo[0].op.memset_0
     assert (numpy.asarray(f(2)) == 1).all()
+
+
+def test_rebroadcast():
+    d = numpy.random.rand(10, 10).astype('float32')
+    v = theano.tensor.fmatrix()
+    up = tensor.unbroadcast(v.sum().dimshuffle('x', 'x'), 0, 1)
+    f = theano.function([v], [up], mode=mode_with_gpu)
+
+    f(d)
+
+    topo = f.maker.fgraph.toposort()
+    rebrs = [node for node in topo if isinstance(node.op, tensor.Rebroadcast)]
+    assert len(rebrs) == 1
+    rebr = rebrs[0]
+
+    assert isinstance(rebr.inputs[0].type, GpuArrayType)
+    assert isinstance(rebr.outputs[0].type, GpuArrayType)