Add some tests (that all fail due to shape errors at the moment).

theano/sandbox/cuda/tests/test_fftconv.py

+import theano
+from theano.tensor import ftensor4
+from theano.tensor.nnet.tests.test_conv import TestConv2D
+
+# Skip tests if cuda_ndarray is not available.
+from nose.plugins.skip import SkipTest
+import theano.sandbox.cuda as cuda_ndarray
+if cuda_ndarray.cuda_available == False:
+    raise SkipTest('Optional package cuda disabled')
+
+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')
+
+class GTestConv2D(TestConv2D):
+    mode = mode_with_gpu
+    dtype = 'float32'
+
+    def setUp(self):
+        super(GTestConv2D, self).setUp()
+        self.input = ftensor4('input')
+        self.filters = ftensor4('filters')
+

theano/tensor/nnet/tests/test_conv.py

@@ -12,9 +12,11 @@ from theano.tensor.basic import _allclose, NotScalarConstantError
 
 
 class TestConv2D(utt.InferShapeTester):
+    mode = None
+    dtype = 'float64'
 
     def setUp(self):
-        super (TestConv2D, self).setUp()
+        super(TestConv2D, self).setUp()
         self.input = T.dtensor4('input')
         self.input.name = 'default_V'
         self.filters = T.dtensor4('filters')
@@ -67,11 +69,11 @@ class TestConv2D(utt.InferShapeTester):
 
         output = sym_conv2d(input, filters)
         output.name = 'conv2d(%s,%s)' % (input.name, filters.name)
-        theano_conv = theano.function([input, filters], output)
+        theano_conv = theano.function([input, filters], output, mode=self.mode)
 
         # initialize input and compute result
-        image_data = numpy.random.random(N_image_shape)
-        filter_data = numpy.random.random(N_filter_shape)
+        image_data = numpy.random.random(N_image_shape).astype(self.dtype)
+        filter_data = numpy.random.random(N_filter_shape).astype(self.dtype)
         try:
             theano_output = theano_conv(image_data, filter_data)
         except ValueError: