flake8 theano/gof/opt.py; 2 E left

theano/gof/opt.py

@@ -29,6 +29,7 @@ from . import destroyhandler as dh
 _logger = logging.getLogger('theano.gof.opt')
 _optimizer_idx = [0]
 
+
 def _list_of_nodes(fgraph):
     return list(graph.io_toposort(fgraph.inputs, fgraph.outputs))
 
@@ -729,6 +730,7 @@ def pre_constant_merge(vars):
     const_sig_inv = {}
     if isinstance(vars, graph.Variable):
         vars = [vars]
+
     def recursive_merge(var):
         if var in seen_var:
             return var
@@ -761,7 +763,7 @@ def pre_constant_merge(vars):
 
 
 ########################
-### Local Optimizers ###
+#   Local Optimizers   #
 ########################
 
 class LocalOptimizer(object):
@@ -820,9 +822,11 @@ class LocalOptimizer(object):
             (' ' * level), self.__class__.__name__, id(self)), file=stream)
 
 
-theano.configparser.AddConfigVar('metaopt.verbose',
+theano.configparser.AddConfigVar(
+    'metaopt.verbose',
     "Enable verbose output for meta optimizers",
-        theano.configparser.BoolParam(False), in_c_key=False)
+    theano.configparser.BoolParam(False),
+    in_c_key=False)
 
 
 class LocalMetaOptimizer(LocalOptimizer):
@@ -1217,6 +1221,7 @@ class PatternSub(LocalOptimizer):
         if node.op != self.op:
             return False
         # TODO: if we remove pdb, do this speed things up?
+
         def match(pattern, expr, u, allow_multiple_clients=False, pdb=False):
             # TODO move outside match
             def retry_with_equiv():
@@ -1233,9 +1238,8 @@ class PatternSub(LocalOptimizer):
             if isinstance(pattern, (list, tuple)):
                 if expr.owner is None:
                     return False
-                if (not (expr.owner.op == pattern[0])
-                        or (not allow_multiple_clients
-                            and len(expr.clients) > 1)):
+                if (not (expr.owner.op == pattern[0]) or
+                        (not allow_multiple_clients and len(expr.clients) > 1)):
                     return retry_with_equiv()
                 if len(pattern) - 1 != len(expr.owner.inputs):
                     return retry_with_equiv()
@@ -1263,16 +1267,16 @@ class PatternSub(LocalOptimizer):
                     return retry_with_equiv()
                 else:
                     u = u.merge(expr, v)
-            elif (isinstance(pattern, (int, float))
-                    and isinstance(expr, graph.Constant)):
+            elif (isinstance(pattern, (int, float)) and
+                    isinstance(expr, graph.Constant)):
                 if numpy.all(
                         theano.tensor.constant(pattern).value == expr.value):
                     return u
                 else:
                     return retry_with_equiv()
-            elif (isinstance(pattern, graph.Constant)
-                    and isinstance(expr, graph.Constant)
-                    and pattern.equals(expr)):
+            elif (isinstance(pattern, graph.Constant) and
+                    isinstance(expr, graph.Constant) and
+                    pattern.equals(expr)):
                 return u
             else:
                 return retry_with_equiv()
@@ -1335,7 +1339,7 @@ class PatternSub(LocalOptimizer):
 
 
 ##################
-### Navigators ###
+#   Navigators   #
 ##################
 
 # Use the following classes to apply LocalOptimizers
@@ -1811,8 +1815,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
                     node_created[gopt] += change_tracker.nb_imported - nb
                     if global_process_count[gopt] > max_use:
                         max_use_abort = True
-                        opt_name = (getattr(gopt, "name", None)
-                                    or getattr(gopt, "__name__", ""))
+                        opt_name = (getattr(gopt, "name", None) or
+                                    getattr(gopt, "__name__", ""))
             global_sub_profs.append(sub_profs)
 
             global_opt_timing.append(float(time.time() - t0))
@@ -1858,8 +1862,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
                             node_created[lopt] += change_tracker.nb_imported - nb
                             if global_process_count[lopt] > max_use:
                                 max_use_abort = True
-                                opt_name = (getattr(lopt, "name", None)
-                                            or getattr(lopt, "__name__", ""))
+                                opt_name = (getattr(lopt, "name", None) or
+                                            getattr(lopt, "__name__", ""))
                             if node not in fgraph.apply_nodes:
                                 # go to next node
                                 break
@@ -1884,8 +1888,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
                     node_created[gopt] += change_tracker.nb_imported - nb
                     if global_process_count[gopt] > max_use:
                         max_use_abort = True
-                        opt_name = (getattr(gopt, "name", None)
-                                    or getattr(gopt, "__name__", ""))
+                        opt_name = (getattr(gopt, "name", None) or
+                                    getattr(gopt, "__name__", ""))
             final_sub_profs.append(sub_profs)
 
             global_opt_timing[-1] += time.time() - t_before_final_opt
@@ -1896,9 +1900,9 @@ class EquilibriumOptimizer(NavigatorOptimizer):
         end_nb_nodes = len(fgraph.apply_nodes)
 
         if max_use_abort:
-            _logger.error("EquilibriumOptimizer max'ed out by '%s'" % opt_name
-                          + ". You can safely raise the current threshold of "
-                          + "%f with the theano flag 'optdb.max_use_ratio'." %
+            _logger.error("EquilibriumOptimizer max'ed out by '%s'" % opt_name +
+                          ". You can safely raise the current threshold of " +
+                          "%f with the theano flag 'optdb.max_use_ratio'." %
                           config.optdb.max_use_ratio)
         fgraph.remove_feature(change_tracker)
         return (self, loop_timing, loop_process_count,
@@ -1975,8 +1979,9 @@ class EquilibriumOptimizer(NavigatorOptimizer):
                 not_used_time += time_opts[o]
 
         if count_opt:
-            print(blanc, \
-                    '  times - times applied - nb node created - name:', file=stream)
+            print(blanc,
+                  '  times - times applied - nb node created - name:',
+                  file=stream)
             count_opt.sort()
             for (t, count, n_created, o) in count_opt[::-1]:
                 print(blanc, '  %.3fs - %d - %d - %s' % (
@@ -2010,7 +2015,7 @@ class EquilibriumOptimizer(NavigatorOptimizer):
 
     @staticmethod
     def merge_profile(prof1, prof2):
-        #(opt, loop_timing, loop_process_count, max_nb_nodes,
+        # (opt, loop_timing, loop_process_count, max_nb_nodes,
         # global_opt_timing, nb_nodes, time_opts, io_toposort_timing) = prof1
         local_optimizers = OrderedSet(prof1[0].get_local_optimizers()).union(
             prof2[0].get_local_optimizers())
@@ -2085,7 +2090,7 @@ class EquilibriumOptimizer(NavigatorOptimizer):
                 final_sub_profs)
 
 #################
-### Utilities ###
+#   Utilities   #
 #################
 
 
@@ -2096,7 +2101,7 @@ def _check_chain(r, chain):
     while chain:
         elem = chain.pop()
         if elem is None:
-            if not r.owner is None:
+            if r.owner is not None:
                 return False
         elif r.owner is None:
             return False
@@ -2105,20 +2110,20 @@ def _check_chain(r, chain):
                 return False
         else:
             try:
-                if (issubclass(elem, op.Op)
-                        and not isinstance(r.owner.op, elem)):
+                if (issubclass(elem, op.Op) and
+                        not isinstance(r.owner.op, elem)):
                     return False
             except TypeError:
                 return False
         if chain:
             r = r.owner.inputs[chain.pop()]
     # print 'check_chain', _check_chain.n_calls
-    #_check_chain.n_calls += 1
+    # _check_chain.n_calls += 1
 
     # The return value will be used as a Boolean, but some Variables cannot
     # be used as Booleans (the results of comparisons, for instance)
     return (r is not None)
-#_check_chain.n_calls = 0
+# _check_chain.n_calls = 0
 
 
 def check_chain(r, *chain):

theano/tests/test_flake8.py

@@ -244,7 +244,6 @@ whitelist_flake8 = [
     "gof/unify.py",
     "gof/graph.py",
     "gof/__init__.py",
-    "gof/opt.py",
     "gof/link.py",
     "gof/fg.py",
     "gof/op.py",