Use random values in test.

theano/sandbox/cuda/tests/test_basic_ops.py

@@ -871,31 +871,30 @@ def test_shared_cudandarray():
     assert isinstance(a.type, tcn.CudaNdarrayType)
 
 
-def test_tensordot_reshape():
+class test_tensordot_reshape(unittest.TestCase):
     '''Test alternative tensordot implementation.
 
     Test that the tensordot implementation using dimshuffle, reshape and dot
     gives the same results as the default (numpy) version.
     '''
+
+    def setUp(self):
+        self.rng = numpy.random.RandomState(utt.fetch_seed())
+
+    def test1(self):
         # define some tensors
-    a = numpy.arange(20, dtype=theano.config.floatX) / 20.0
-    b = numpy.arange(10, dtype=theano.config.floatX) / 10.0
-    c = numpy.arange(5, dtype=theano.config.floatX) / 5.0
-    d = numpy.arange(8, dtype=theano.config.floatX) / 8.0
-
-    tensor1 = numpy.tensordot(
-            a,
-            numpy.tensordot(b, numpy.tensordot(c, d, 0), 0),
-            0)
-    tensor2 = numpy.tensordot(c, numpy.tensordot(d, a, 0), 0)
-    tensor3 = tensor2.swapaxes(1, 2).swapaxes(0, 2)  # d, a, c
+        tensor1 = self.rng.rand(20, 10, 5, 8).astype(theano.config.floatX)
+        tensor2 = self.rng.rand(5, 8, 20).astype(theano.config.floatX)
+        tensor3 = self.rng.rand(8, 20, 5).astype(theano.config.floatX)
 
         x = T.tensor4('x')
         y = T.tensor3('y')
 
         # case 1: number of axes to sum over
-    default1 = theano.function([x, y], T.tensordot(x, y, 2))(tensor1, tensor2)
-    reshape1 = theano.function([x, y], B.tensordot(x, y, 2))(tensor1, tensor2)
+        default1 = theano.function([x, y], T.tensordot(x, y, 2))(
+                tensor1, tensor2)
+        reshape1 = theano.function([x, y], B.tensordot(x, y, 2))(
+                tensor1, tensor2)
         assert numpy.allclose(default1, reshape1)
 
         # case 2: axis pairs