Raise ValueErrors instead of AttributeErrors for bad Apply.default_value

tests/tensor/test_basic.py

@@ -2799,11 +2799,11 @@ class TestAsTensorVariable:
         as_tensor_variable(good_apply_var)
 
         bad_apply_var = ApplyDefaultTestOp(-1).make_node(self.x)
-        with pytest.raises(AttributeError):
+        with pytest.raises(ValueError):
             _ = as_tensor_variable(bad_apply_var)
 
         bad_apply_var = ApplyDefaultTestOp(2).make_node(self.x)
-        with pytest.raises(AttributeError):
+        with pytest.raises(ValueError):
             _ = as_tensor_variable(bad_apply_var)
 
     def test_list(self):
@@ -2816,7 +2816,7 @@ class TestAsTensorVariable:
             _ = as_tensor_variable(y)
 
         bad_apply_var = ApplyDefaultTestOp([0, 1]).make_node(self.x)
-        with pytest.raises(AttributeError):
+        with pytest.raises(ValueError):
             as_tensor_variable(bad_apply_var)
 
     def test_strip_leading_broadcastable(self):

theano/gof/graph.py

@@ -165,13 +165,13 @@ class Apply(Node):
             if len(self.outputs) == 1:
                 return self.outputs[0]
             else:
-                raise AttributeError(
+                raise ValueError(
                     "%s.default_output should be an output index." % self.op
                 )
         elif not isinstance(do, integer_types):
-            raise AttributeError("%s.default_output should be an int or long" % self.op)
+            raise ValueError("%s.default_output should be an int or long" % self.op)
         elif do < 0 or do >= len(self.outputs):
-            raise AttributeError("%s.default_output is out of range." % self.op)
+            raise ValueError("%s.default_output is out of range." % self.op)
         return self.outputs[do]
 
     out = property(default_output, doc="alias for self.default_output()")