And make the opt test work.

theano/sandbox/cuda/tests/test_blocksparse.py

+import numpy
+from numpy.random import randn
+
+from unittest import TestCase
+
+from nose.plugins.skip import SkipTest
+
 import theano
 from theano import tensor
 import theano.tests.unittest_tools as utt
 
-import numpy
-from numpy.random import randn
+import theano.sandbox.cuda as cuda_ndarray
+if cuda_ndarray.cuda_available == False:
+    raise SkipTest('Optional package cuda disabled')
 
 from theano.sandbox.cuda.blocksparse import (sparse_block_dot_SS,
                                              sparse_block_gemv_ss,
-                                             sparse_block_gemv_ss_inplace)
+                                             sparse_block_gemv_ss_inplace,
                                              sparse_block_outer_ss,
                                              sparse_block_outer_ss_inplace)
 
+if theano.config.mode == 'FAST_COMPILE':
+    mode_with_gpu = theano.compile.mode.get_mode('FAST_RUN').including('gpu')
+else:
+    mode_with_gpu = theano.compile.mode.get_default_mode().including('gpu')
+
 
 def blocksparse_data():
     nInputBlock = 128
@@ -109,14 +122,14 @@ class TestBlockSparseDot(TestCase, utt.TestOptimizationMixin):
 
         o = sparse_block_dot_SS(W, h, iIdx, b, oIdx)
 
-        f = theano.function([W, h, iIdx, b, oIdx], o)
+        f = theano.function([W, h, iIdx, b, oIdx], o, mode=mode_with_gpu)
 
         self.assertFunctionContains0(f, sparse_block_gemv_ss)
         self.assertFunctionContains1(f, sparse_block_gemv_ss_inplace)
 
         gW = theano.grad(o.sum(), [W])
 
-        f = theano.function([W, h, iIdx, b, oIdx], gW)
+        f = theano.function([W, h, iIdx, b, oIdx], gW, mode=mode_with_gpu)
 
         self.assertFunctionContains0(f, sparse_block_outer_ss)
         self.assertFunctionContains1(f, sparse_block_outer_ss_inplace)