Merge pull request #444 from lamblin/fix_sparse_infershape_tests

theano/sparse/tests/test_basic.py

@@ -95,10 +95,15 @@ class T_transpose(unittest.TestCase):
 class SparseInferShapeTester(unittest.TestCase):
     def setUp(self):
         utt.seed_rng()
+        # This mode seems to be the minimal one including the shape_i
+        # optimizations, if we don't want to enumerate them explicitly.
+        self.mode = theano.compile.get_default_mode().including("canonicalize")
 
     def _compile_and_check(self, inputs, outputs, numeric_inputs, cls):
-        outputs_function = theano.function(inputs, outputs)
-        shapes_function = theano.function(inputs, [o.shape for o in outputs])
+        outputs_function = theano.function(inputs, outputs, mode=self.mode)
+        shapes_function = theano.function(inputs, [o.shape for o in outputs],
+                mode=self.mode)
+        theano.printing.debugprint(shapes_function)
         # Check that the Op is removed from the compiled function.
         topo_shape = shapes_function.maker.env.toposort()
         assert not any(isinstance(t.op, cls) for t in topo_shape)
@@ -161,12 +166,13 @@ class SparseInferShapeTester(unittest.TestCase):
     def test_add_sd(self):
         x = SparseType('csr', dtype=config.floatX)()
         y = tensor.matrix()
-        self._compile_and_check([x, y],
-                                [x + y],
-                                [sp.csr_matrix(random_lil((10, 40),
-                                               config.floatX, 3)),
-                                 numpy.random.randn(10, 40)],
-                                AddSD)
+        self._compile_and_check(
+                [x, y],
+                [x + y],
+                [sp.csr_matrix(random_lil((10, 40),
+                               config.floatX, 3)),
+                 numpy.random.randn(10, 40).astype(config.floatX)],
+                AddSD)
 
     def test_mul_ss(self):
         x = SparseType('csr', dtype=config.floatX)()
@@ -181,12 +187,13 @@ class SparseInferShapeTester(unittest.TestCase):
     def test_mul_sd(self):
         x = SparseType('csr', dtype=config.floatX)()
         y = tensor.matrix()
-        self._compile_and_check([x, y],
-                                [x * y],
-                                [sp.csr_matrix(random_lil((10, 40),
-                                               config.floatX, 3)),
-                                 numpy.random.randn(10, 40)],
-                                MulSD)
+        self._compile_and_check(
+                [x, y],
+                [x * y],
+                [sp.csr_matrix(random_lil((10, 40),
+                               config.floatX, 3)),
+                 numpy.random.randn(10, 40).astype(config.floatX)],
+                MulSD)
 
 
 class T_AddMul(unittest.TestCase):