some pep8

theano/tensor/subtensor.py

@@ -594,8 +594,7 @@ class Subtensor(Op):
     @staticmethod
     def helper_c_code(node, name, inputs, outputs, sub, idx_list, view_ndim,
                       c_prefix=None,
-                      strides_mul=None,
-    ):
+                      strides_mul=None):
         """
         The parameters c_prefix are there to allow reusing this
         function on PyArray and CudaNdarray object.
@@ -682,7 +681,8 @@ class Subtensor(Op):
             subensor_spec = "npy_intp * subtensor_spec = NULL;"
 
         if is_slice:
-            is_slice_init = "int is_slice[] = {" + ",".join([str(s) for s in is_slice]) + "};"
+            is_slice_init = "int is_slice[] = {" + ",".join([str(s) for s in
+                                                             is_slice]) + "};"
         else:
             is_slice_init = "int* is_slice = NULL;"
         subtensor_init = "\n".join(init_cmds)
@@ -897,7 +897,8 @@ class Subtensor(Op):
         %(z)s = xview;
         """ % locals()
 
-        return decl + checkNDim + "{" + get_xview + build_view + finish_view + "}"
+        return (decl + checkNDim +
+                "{" + get_xview + build_view + finish_view + "}")
 
     def c_code_cache_version(self):
         hv = self.helper_c_code_cache_version()
@@ -1022,9 +1023,9 @@ def inc_subtensor(x, y, inplace=False, set_instead_of_inc=False,
             destroyhandler_tolerate_aliased = [[0, 1]]
         else:
             destroyhandler_tolerate_aliased = []
-        the_op = IncSubtensor(x.owner.op.idx_list, inplace, set_instead_of_inc,
-                destroyhandler_tolerate_aliased=destroyhandler_tolerate_aliased
-                )
+        the_op = IncSubtensor(
+            x.owner.op.idx_list, inplace, set_instead_of_inc,
+            destroyhandler_tolerate_aliased=destroyhandler_tolerate_aliased)
         real_x = x.owner.inputs[0]
         real_idxargs = x.owner.inputs[1:]
         return the_op(real_x, y, *real_idxargs)
@@ -1105,10 +1106,10 @@ class IncSubtensor(Op):
         self.set_instead_of_inc = set_instead_of_inc
 
     def __eq__(self, other):
-        return type(self) == type(other) \
-                and self.idx_list == other.idx_list \
-                and self.inplace == other.inplace \
-                and self.set_instead_of_inc == other.set_instead_of_inc
+        return (type(self) == type(other) and
+                self.idx_list == other.idx_list and
+                self.inplace == other.inplace and
+                self.set_instead_of_inc == other.set_instead_of_inc)
 
     def __hash__(self):
         msg = []
@@ -1120,12 +1121,12 @@ class IncSubtensor(Op):
 
         idx_list = tuple(msg)
         # backport
-        #idx_list = tuple((entry.start, entry.stop, entry.step)
+        # idx_list = tuple((entry.start, entry.stop, entry.step)
         #                 if isinstance(entry, slice)
         #                 else entry
         #                 for entry in self.idx_list)
-        return hashtype(self) ^ hash(idx_list) ^ hash(self.inplace) \
-               ^ hash(self.set_instead_of_inc)
+        return (hashtype(self) ^ hash(idx_list) ^ hash(self.inplace) ^
+                hash(self.set_instead_of_inc))
 
     def __str__(self):
         indices = []
@@ -1225,7 +1226,7 @@ class IncSubtensor(Op):
             if not self.set_instead_of_inc:
                 sub_x += y
             else:
-                #sub_x += -sub_x + y
+                # sub_x += -sub_x + y
                 x.__setitem__(cdata, y)
         else:
             # scalar case
@@ -1469,7 +1470,7 @@ class IncSubtensor(Op):
                     axis_to_sum.append(i)
                 elif (gy.broadcastable[i] is True and
                       y_broad[i] is False):
-                    # This mean that THeano where able to infer that
+                    # This mean that Theano where able to infer that
                     # gy.shape[i] is 1, so y.shape[i] is 1, but we
                     # didn't know it. It is fine.
                     pass

theano/tensor/tests/test_inc_subtensor.py

@@ -83,11 +83,11 @@ class Test_inc_subtensor(unittest.TestCase):
                 f(rng_randX(3, 1), rng_randX(1))
                 # These ones should not
                 self.assertRaises(ValueError,
-                        f, rng_randX(3, 1), rng_randX(2))
+                                  f, rng_randX(3, 1), rng_randX(2))
                 self.assertRaises(ValueError,
-                        f, rng_randX(3, 1), rng_randX(3))
+                                  f, rng_randX(3, 1), rng_randX(3))
                 self.assertRaises(ValueError,
-                        f, rng_randX(3, 1), rng_randX(0))
+                                  f, rng_randX(3, 1), rng_randX(0))
 
     def test_simple_3d(self):
         """Increments or sets part of a tensor by a scalar using full slice and
@@ -150,21 +150,21 @@ class Test_inc_subtensor(unittest.TestCase):
         for f_slice in [inc_slice, set_slice]:
             # vector
             utt.verify_grad(
-                    f_slice(slice(2, 4, None)),
-                    (numpy.asarray([0, 1, 2, 3, 4, 5.]),
-                        numpy.asarray([9, 9.]), ))
+                f_slice(slice(2, 4, None)),
+                (numpy.asarray([0, 1, 2, 3, 4, 5.]),
+                 numpy.asarray([9, 9.]), ))
 
             # matrix
             utt.verify_grad(
-                    f_slice(slice(1, 2, None), slice(None, None, None)),
-                    (numpy.asarray([[0, 1], [2, 3], [4, 5.]]),
-                        numpy.asarray([[9, 9.]]), ))
+                f_slice(slice(1, 2, None), slice(None, None, None)),
+                (numpy.asarray([[0, 1], [2, 3], [4, 5.]]),
+                 numpy.asarray([[9, 9.]]), ))
 
-            #single element
+            # single element
             utt.verify_grad(
-                    f_slice(2, 1),
-                    (numpy.asarray([[0, 1], [2, 3], [4, 5.]]),
-                        numpy.asarray(9.),))
+                f_slice(2, 1),
+                (numpy.asarray([[0, 1], [2, 3], [4, 5.]]),
+                 numpy.asarray(9.),))
 
             # broadcast
             utt.verify_grad(