Tests for cast.

theano/tensor/tests/test_basic.py

@@ -870,6 +870,14 @@ def multi_dtype_tests(shape1, shape2, dtypes=ALL_DTYPES, nameprefix=''):
         yield (name, (obj1, obj2))
         yield (name, (obj2, obj1))
 
+def multi_dtype_cast_tests(shape, dtypes=ALL_DTYPES, nameprefix=''):
+    for dtype1, dtype2 in combinations(dtypes, 2):
+        name1 = '%s_%s_%s' % (nameprefix, dtype1, dtype2)
+        name2 = '%s_%s_%s' % (nameprefix, dtype2, dtype1)
+        obj1 = rand_of_dtype(shape, dtype1)
+        yield (name, (obj1, dtype2))
+        yield (name, (obj2, dtype1))
+
 SecondBroadcastTester = makeTester(
                             name='SecondBroadcastTester',
                             op=second,
@@ -903,6 +911,22 @@ SecondSameRankTester = makeTester(
                             bad_runtime=None
                         )
 
+CastTester = makeTester(
+                name='CastTester',
+                op=cast,
+                expected=lambda x, y: x.astype(y),
+                good=dict(itertools.chain(
+                    multi_dtype_cast_tests((2,)),
+                    [('%s_%s' % (dtype, dtype), rand_of_dtype((2,), dtype), dtype)
+                     for dtype in ALL_DTYPES]
+                )),
+                bad_build=dict(
+                    fail_not_a_real_dtype=((2,), 'blah')
+                ),
+                bad_runtime=None
+            )
+
+
 #TODO: consider moving this function / functionality to gradient.py
 #      rationale: it's tricky, and necessary everytime you want to verify
 #      gradient numerically