Port forward my cast tester that I actually quashed in a merge.

theano/tensor/tests/test_basic.py

@@ -819,6 +819,8 @@ def combinations(iterable, r):
 
 ALL_DTYPES = ('int8', 'int16', 'int32', 'int64',
               'float32', 'float64', 'complex64', 'complex128')
+REAL_DTYPES = ALL_DTYPES[:-2]
+COMPLEX_DTYPES = ALL_DTYPES[-2:]
 
 def rand_of_dtype(shape, dtype):
     if 'int' in dtype:
@@ -882,18 +884,35 @@ SecondSameRankTester = makeTester(
                             ))
                         )
 
-CastTester = makeTester(
-                name='CastTester',
-                op=cast,
-                expected=lambda x, y: x.astype(y),
-                good=dict(itertools.chain(
-                    multi_dtype_cast_checks((2,)),
+class CastTester(unittest.TestCase):
+    def test_good_between_real_types(self):
+        expected = lambda x, y: x.astype(y),
+        good = itertools.chain(
+                    multi_dtype_cast_checks((2,), dtypes=REAL_DTYPES),
                     # Casts from foo to foo
                     [('%s_%s' % (rand_of_dtype((2,), dtype), dtype),
                       (rand_of_dtype((2,), dtype), dtype))
-                     for dtype in ALL_DTYPES]
-                )),
-            )
+                     for dtype in ALL_DTYPES])
+        for testname, (obj, dtype) in good:
+            inp = tensor.vector(dtype=obj.dtype)
+            out = tensor.cast(inp, dtype=dtype)
+            f = function([inp], out)
+            assert f(obj).dtype == numpy.dtype(dtype)
+
+    def test_cast_from_real_to_complex(self):
+        for real_dtype in REAL_DTYPES:
+            for complex_dtype in COMPLEX_DTYPES:
+                inp = tensor.vector(dtype=real_dtype)
+                out = tensor.cast(inp, dtype=complex_dtype)
+                f = function([inp], out)
+                obj = rand_of_dtype((2, ), real_dtype)
+                assert f(obj).dtype == numpy.dtype(complex_dtype)
+
+    def test_cast_from_complex_to_real_raises_error(self):
+        for real_dtype in REAL_DTYPES:
+            for complex_dtype in COMPLEX_DTYPES:
+                inp = tensor.vector(dtype=real_dtype)
+                self.assertRaises(TypeError, tensor.cast(inp, dtype=complex_dtype))
 
 ClipTester = makeTester(name='ClipTester',
                         op=clip,