Fixed some test with numpy 1.5.1 under Windows

theano/tensor/tests/test_basic.py

@@ -72,7 +72,7 @@ def get_numeric_subclasses(cls=numpy.number, ignore=None):
 
 
 def get_numeric_types(with_int=True, with_float=True, with_complex=False,
-                      with_128_bit=False):
+                      only_theano_types=True):
     """
     Return numpy numeric data types.
 
@@ -82,17 +82,21 @@ def get_numeric_types(with_int=True, with_float=True, with_complex=False,
 
     :param with_complex: Whether to include complex types.
 
-    :param with_128_bit: Whether to include 128/256-bit types.
+    :param only_theano_types: If True, then numpy numeric data types that are
+    not supported by Theano are ignored (i.e. those that are not declared in
+    scalar/basic.py).
 
     :returns: A list of unique data type objects. Note that multiple data types
     may share the same string representation, but can be differentiated through
     their `num` attribute.
 
-    Note that we could probably rely on the lists of types defined in the
-    `scalar` module. However with this function we can test more unique dtype
-    objects, and possibly detect defects in dtypes that may be introduced in
-    numpy in the future.
+    Note that when `only_theano_types` is True we could simply return the list
+    of types defined in the `scalar` module. However with this function we can
+    test more unique dtype objects, and in the future we may use it to
+    automatically detect new data types introduced in numpy.
     """
+    if only_theano_types:
+        theano_types = [d.dtype for d in theano.scalar.all_types]
     rval = []
     def is_within(cls1, cls2):
         # Return True if scalars defined from `cls1` are within the hierarchy
@@ -109,8 +113,7 @@ def get_numeric_types(with_int=True, with_float=True, with_complex=False,
         if ((not with_complex and is_within(cls, numpy.complexfloating)) or
             (not with_int and is_within(cls, numpy.integer)) or
             (not with_float and is_within(cls, numpy.floating)) or
-            (not with_128_bit and ('128' in str(dtype) or
-                                   '256' in str(dtype)))):
+            (only_theano_types and dtype not in theano_types)):
             # Ignore this class.
             continue
         rval.append([str(dtype), dtype, dtype.num])
@@ -4566,6 +4569,10 @@ class test_arithmetic_cast(unittest.TestCase):
         numpy_array = lambda dtype: numpy.array([1], dtype=dtype)
         theano_i_scalar = lambda dtype: theano.scalar.Scalar(str(dtype))()
         numpy_i_scalar = numpy_scalar
+        if config.int_division == 'int':
+            # Avoid deprecation warning during tests.
+            warnings.filterwarnings('ignore', message='Division of two integer',
+                                    category=DeprecationWarning)
         try:
             for cfg in ('numpy+floatX', ): # Used to test 'numpy' as well.
                 config.cast_policy = cfg
@@ -4666,7 +4673,13 @@ class test_arithmetic_cast(unittest.TestCase):
                                 assert False
         finally:
             config.cast_policy = backup_config
-
+            if config.int_division == 'int':
+                # Restore default deprecation warning behavior.
+                warnings.filterwarnings(
+                        'default',
+                        message='Division of two integer',
+                        category=DeprecationWarning)
+ 
 
 class test_broadcast(unittest.TestCase):
     def test_broadcast_bigdim(self):