Check that TypeError is raised when sum downcasts

theano/tensor/tests/test_elemwise.py

@@ -499,7 +499,8 @@ class test_IsInf_IsNan(unittest.TestCase):
         return self.run_isfunc('isnan')
 
 
-def test_sum_default_dtype():
+class T_sum_dtype(unittest.TestCase):
+    def test_sum_default_dtype(self):
         """
         Test the default dtype of a sum().
         """
@@ -517,8 +518,7 @@ def test_sum_default_dtype():
                     uint32='uint64',
                     ).get(dtype, dtype)
 
-
-def test_sum_custom_dtype():
+    def test_sum_custom_dtype(self):
         """
         Test the ability to provide your own output dtype for a sum.
         """
@@ -529,7 +529,19 @@ def test_sum_custom_dtype():
             x = tensor.matrix(dtype=input_dtype)
             for output_dtype in imap(str, theano.scalar.all_types):
                 axis = axes[idx % len(axes)]
-            assert x.sum(dtype=output_dtype, axis=axis).dtype == output_dtype
+                # If output_dtype would force a downcast, we expect a TypeError
+                # We always allow int/uint inputs with float/complex outputs.
+                upcasted_dtype = scalar.upcast(input_dtype, output_dtype)
+                if (output_dtype == upcasted_dtype or
+                        (input_dtype in discrete_dtypes and
+                            output_dtype in continuous_dtypes)
+                        ):
+                    sum_var = x.sum(dtype=output_dtype, axis=axis)
+                    assert sum_var.dtype == output_dtype
+                else:
+                    self.assertRaises(TypeError,
+                            x.sum, dtype=output_dtype, axis=axis)
+
                 idx += 1