Use random values in test.

theano/sandbox/cuda/tests/test_basic_ops.py

@@ -871,53 +871,52 @@ 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.
     '''
-    # 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
-
-    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)
-    assert numpy.allclose(default1, reshape1)
-
-    # case 2: axis pairs
-    default2 = theano.function(
-            [x, y],
-            T.tensordot(x, y, axes=[(0, 3), (1, 0)])
-            )(tensor1, tensor3)
-    reshape2 = theano.function(
-            [x, y],
-            B.tensordot(x, y, axes=[(0, 3), (1, 0)])
-            )(tensor1, tensor3)
-    assert numpy.allclose(default2, reshape2)
-
-    default3 = theano.function(
-            [x, y],
-            T.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)])
-            )(tensor1, tensor3)
-    reshape3 = theano.function(
-            [x, y],
-            B.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)])
-            )(tensor1, tensor3)
-    assert numpy.allclose(default3, reshape3)
+
+    def setUp(self):
+        self.rng = numpy.random.RandomState(utt.fetch_seed())
+
+    def test1(self):
+        # define some tensors
+        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)
+        assert numpy.allclose(default1, reshape1)
+
+        # case 2: axis pairs
+        default2 = theano.function(
+                [x, y],
+                T.tensordot(x, y, axes=[(0, 3), (1, 0)])
+                )(tensor1, tensor3)
+        reshape2 = theano.function(
+                [x, y],
+                B.tensordot(x, y, axes=[(0, 3), (1, 0)])
+                )(tensor1, tensor3)
+        assert numpy.allclose(default2, reshape2)
+
+        default3 = theano.function(
+                [x, y],
+                T.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)])
+                )(tensor1, tensor3)
+        reshape3 = theano.function(
+                [x, y],
+                B.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)])
+                )(tensor1, tensor3)
+        assert numpy.allclose(default3, reshape3)
 
 
 class test_size(unittest.TestCase):