Fix the arange tests to expect the right dtype.

theano/tensor/tests/test_basic.py

@@ -5316,7 +5316,7 @@ class TestARange(unittest.TestCase):
         f = function([start, stop, step], out)
 
         if config.cast_policy == 'custom':
-            assert out.dtype == start.type.dtype
+            assert out.dtype == 'int64'
         elif config.cast_policy in ('numpy', 'numpy+floatX'):
             numpy_dtype = numpy.arange(numpy.array(1, dtype='int32')).dtype
             assert out.dtype == numpy_dtype
@@ -5393,7 +5393,7 @@ class TestARange(unittest.TestCase):
         f = function([start, stop], out)
 
         if config.cast_policy == 'custom':
-            assert out.dtype == start.type.dtype
+            assert out.dtype == 'int64'
         elif config.cast_policy in ('numpy', 'numpy+floatX'):
             assert out.dtype == numpy.arange(numpy.int32(0),
                                              numpy.int32(1)).dtype
@@ -5421,7 +5421,7 @@ class TestARange(unittest.TestCase):
         f = function([stop], out)
 
         if config.cast_policy == 'custom':
-            assert out.dtype == stop.type.dtype
+            assert out.dtype == 'int64'
         elif config.cast_policy in ('numpy', 'numpy+floatX'):
             assert out.dtype == numpy.arange(numpy.int32(1)).dtype
         else:
@@ -5453,7 +5453,7 @@ class TestARange(unittest.TestCase):
     def test_upcast(self):
         """Test that arange computes output type adequately"""
         if config.cast_policy == 'custom':
-            assert arange(iscalar()).dtype == iscalar().dtype
+            assert arange(iscalar()).dtype == 'int64'
             assert arange(fscalar()).dtype == fscalar().dtype
             assert arange(dscalar()).dtype == dscalar().dtype
 
@@ -5547,7 +5547,7 @@ class TestARange(unittest.TestCase):
         assert len(f.maker.fgraph.toposort()) == 9
 
         if config.cast_policy == 'custom':
-            assert out.dtype == start.type.dtype
+            assert out.dtype == 'int64'
         elif config.cast_policy in ('numpy', 'numpy+floatX'):
             numpy_dtype = numpy.arange(numpy.array(0, dtype=start.dtype),
                                        numpy.array(1, dtype=stop.dtype),
@@ -5568,7 +5568,7 @@ class TestARange(unittest.TestCase):
         assert len(f.maker.fgraph.toposort()) == 5
 # 4 [Elemwise{sub,no_inplace}(stop, start), Elemwise{Cast{int64}}(Elemwise{sub,no_inplace}.0), Elemwise{Maximum{output_types_preference=transfer_type{0}}}[(0, 0)](Elemwise{Cast{int64}}.0, 0), MakeVector(Elemwise{Maximum{output_types_preference=transfer_type{0}}}[(0, 0)].0)]
         if config.cast_policy == 'custom':
-            assert out.dtype == start.type.dtype
+            assert out.dtype == 'int64'
         elif config.cast_policy in ('numpy', 'numpy+floatX'):
             assert out.dtype == numpy.arange(
                     numpy.int32(0), numpy.int32(1), numpy.int32(1)).dtype
@@ -5590,7 +5590,7 @@ class TestARange(unittest.TestCase):
         #[Elemwise{Cast{int64}}(stop), MakeVector(Elemwise{Cast{int64}}.0)]
 
         if config.cast_policy == 'custom':
-            assert out.dtype == start.type.dtype
+            assert out.dtype == 'int64'
         elif config.cast_policy in ('numpy', 'numpy+floatX'):
             numpy_dtype = numpy.arange(0,
                                        numpy.array(1, dtype=stop.dtype),