Fix almost all the tests.

theano/tensor/tests/test_basic.py

@@ -4996,7 +4996,7 @@ class T_scalarfromtensor(unittest.TestCase):
 
         self.assertTrue(v == 56, v)
         if config.cast_policy == 'custom':
-            self.assertTrue(isinstance(v, numpy.int16))
+            self.assertTrue(isinstance(v, numpy.int8))
         elif config.cast_policy in ('numpy', 'numpy+floatX'):
             self.assertTrue(isinstance(
                 v, getattr(numpy, str(numpy.asarray(56).dtype))))
@@ -7108,7 +7108,7 @@ class T_as_tensor_variable(unittest.TestCase):
 
     def test_ndarray_bool(self):
         ten = as_tensor_variable(numpy.array([True, False, False, True, True]))
-        assert ten.type.dtype == 'uint8'
+        assert ten.type.dtype == 'bool'
 
     def test_memmap(self):
         inp = numpy.random.rand(4, 3)

theano/tensor/tests/test_elemwise.py

@@ -812,6 +812,7 @@ class T_reduce_dtype(unittest.TestCase):
 
     def test_reduce_default_acc_dtype(self):
         # Test the default acc_dtype of a reduce().
+
         # We try multiple axis combinations even though axis should not matter.
         for method in self.methods:
             for idx, dtype in enumerate(self.dtypes):
@@ -839,6 +840,7 @@ class T_reduce_dtype(unittest.TestCase):
     @attr('slow')
     def test_reduce_custom_dtype(self):
         # Test the ability to provide your own output dtype for a reduce.
+
         # We try multiple axis combinations even though axis should not matter.
         idx = 0
         for method in self.methods:
@@ -872,6 +874,7 @@ class T_reduce_dtype(unittest.TestCase):
 
     def test_reduce_custom_acc_dtype(self):
         # Test the ability to provide your own accumulator dtype for a reduce.
+
         # We try multiple axis combinations even though axis should not matter.
         idx = 0
         for method in self.methods:
@@ -928,9 +931,8 @@ class T_reduce_dtype(unittest.TestCase):
 
 class T_mean_dtype(unittest.TestCase):
     def test_mean_default_dtype(self):
-        """
-        Test the default dtype of a mean().
-        """
+        # Test the default dtype of a mean().
+
         # We try multiple axis combinations even though axis should not matter.
         axes = [None, 0, 1, [], [0], [1], [0, 1]]
         for idx, dtype in enumerate(imap(str, theano.scalar.all_types)):
@@ -948,9 +950,8 @@ class T_mean_dtype(unittest.TestCase):
 
     @attr('slow')
     def test_mean_custom_dtype(self):
-        """
-        Test the ability to provide your own output dtype for a mean.
-        """
+        # Test the ability to provide your own output dtype for a mean.
+
         # We try multiple axis combinations even though axis should not matter.
         axes = [None, 0, 1, [], [0], [1], [0, 1]]
         idx = 0
@@ -1007,9 +1008,8 @@ class T_mean_dtype(unittest.TestCase):
 
 class T_prod_without_zeros_dtype(unittest.TestCase):
     def test_prod_without_zeros_default_dtype(self):
-        """
-        Test the default dtype of a ProdWithoutZeros().
-        """
+        # Test the default dtype of a ProdWithoutZeros().
+
         # We try multiple axis combinations even though axis should not matter.
         axes = [None, 0, 1, [], [0], [1], [0, 1]]
         for idx, dtype in enumerate(imap(str, theano.scalar.all_types)):
@@ -1025,9 +1025,8 @@ class T_prod_without_zeros_dtype(unittest.TestCase):
             ).get(dtype, dtype)
 
     def test_prod_without_zeros_default_acc_dtype(self):
-        """
-        Test the default dtype of a ProdWithoutZeros().
-        """
+        # Test the default dtype of a ProdWithoutZeros().
+
         # We try multiple axis combinations even though axis should not matter.
         axes = [None, 0, 1, [], [0], [1], [0, 1]]
         for idx, dtype in enumerate(imap(str, theano.scalar.all_types)):
@@ -1055,9 +1054,8 @@ class T_prod_without_zeros_dtype(unittest.TestCase):
 
     @attr('slow')
     def test_prod_without_zeros_custom_dtype(self):
-        """
-        Test ability to provide your own output dtype for a ProdWithoutZeros().
-        """
+        # Test ability to provide your own output dtype for a ProdWithoutZeros().
+
         # We try multiple axis combinations even though axis should not matter.
         axes = [None, 0, 1, [], [0], [1], [0, 1]]
         idx = 0
@@ -1079,9 +1077,8 @@ class T_prod_without_zeros_dtype(unittest.TestCase):
 
     @attr('slow')
     def test_prod_without_zeros_custom_acc_dtype(self):
-        """
-        Test ability to provide your own acc_dtype for a ProdWithoutZeros().
-        """
+        # Test ability to provide your own acc_dtype for a ProdWithoutZeros().
+
         # We try multiple axis combinations even though axis should not matter.
         axes = [None, 0, 1, [], [0], [1], [0, 1]]
         idx = 0

theano/tensor/type.py

@@ -341,7 +341,7 @@ class TensorType(Type):
                 return False
             if a.dtype != b.dtype:
                 return False
-            if 'float' not in str(a.dtype):
+            if str(a.dtype) not in theano.tensor.continuous_dtypes:
                 return numpy.all(a == b)
             else:
                 cmp = theano.tensor.basic._allclose(a, b, rtol=rtol, atol=atol)