Add C0330 bad-continuation check to pylint.

PiperOrigin-RevId: 183270896

1 files changed, 34 insertions, 41 deletions

diff --git a/tensorflow/contrib/copy_graph/python/util/copy_elements.py b/tensorflow/contrib/copy_graph/python/util/copy_elements.py
index bae66ffd42..b806799202 100644
--- a/tensorflow/contrib/copy_graph/python/util/copy_elements.py
+++ b/tensorflow/contrib/copy_graph/python/util/copy_elements.py
@@ -35,10 +35,10 @@ from tensorflow.python.ops.variables import Variable
 from tensorflow.python.client.session import Session
 from tensorflow.python.framework import ops
 
-__all__ = ["copy_op_to_graph", "copy_variable_to_graph", "get_copied_op"]
+__all__ = ['copy_op_to_graph', 'copy_variable_to_graph', 'get_copied_op']
 
 
-def copy_variable_to_graph(org_instance, to_graph, scope=""):
+def copy_variable_to_graph(org_instance, to_graph, scope=''):
   """Given a `Variable` instance from one `Graph`, initializes and returns
   a copy of it from another `Graph`, under the specified scope
   (default `""`).
@@ -56,12 +56,11 @@ def copy_variable_to_graph(org_instance, to_graph, scope=""):
   """
 
   if not isinstance(org_instance, Variable):
-    raise TypeError(str(org_instance) + " is not a Variable")
+    raise TypeError(str(org_instance) + ' is not a Variable')
 
   #The name of the new variable
-  if scope != "":
-    new_name = (scope + '/' +
-                org_instance.name[:org_instance.name.index(':')])
+  if scope != '':
+    new_name = (scope + '/' + org_instance.name[:org_instance.name.index(':')])
   else:
     new_name = org_instance.name[:org_instance.name.index(':')]
 
@@ -73,15 +72,15 @@ def copy_variable_to_graph(org_instance, to_graph, scope=""):
   for name, collection in org_instance.graph._collections.items():
     if org_instance in collection:
       if (name == ops.GraphKeys.GLOBAL_VARIABLES or
-          name == ops.GraphKeys.TRAINABLE_VARIABLES or
-          scope == ''):
+          name == ops.GraphKeys.TRAINABLE_VARIABLES or scope == ''):
         collections.append(name)
       else:
         collections.append(scope + '/' + name)
 
   #See if its trainable.
-  trainable = (org_instance in org_instance.graph.get_collection(
-      ops.GraphKeys.TRAINABLE_VARIABLES))
+  trainable = (
+      org_instance in org_instance.graph.get_collection(
+          ops.GraphKeys.TRAINABLE_VARIABLES))
   #Get the initial value
   with org_instance.graph.as_default():
     temp_session = Session()
@@ -89,17 +88,17 @@ def copy_variable_to_graph(org_instance, to_graph, scope=""):
 
   #Initialize the new variable
   with to_graph.as_default():
-    new_var = Variable(init_value,
-                       trainable,
-                       name=new_name,
-                       collections=collections,
-                       validate_shape=False)
+    new_var = Variable(
+        init_value,
+        trainable,
+        name=new_name,
+        collections=collections,
+        validate_shape=False)
 
   return new_var
 
 
-def copy_op_to_graph(org_instance, to_graph, variables,
-                     scope=""):
+def copy_op_to_graph(org_instance, to_graph, variables, scope=''):
   """Returns a copy of an operation from another Graph under a specified scope.
 
   Given an `Operation` `org_instance` from one `Graph`,
@@ -139,14 +138,12 @@ def copy_op_to_graph(org_instance, to_graph, variables,
   #If a variable by the new name already exists, return the
   #correspondng tensor that will act as an input
   if new_name in copied_variables:
-    return to_graph.get_tensor_by_name(
-        copied_variables[new_name].name)
+    return to_graph.get_tensor_by_name(copied_variables[new_name].name)
 
   #If an instance of the same name exists, return appropriately
   try:
-    already_present = to_graph.as_graph_element(new_name,
-                                                allow_tensor=True,
-                                                allow_operation=True)
+    already_present = to_graph.as_graph_element(
+        new_name, allow_tensor=True, allow_operation=True)
     return already_present
   except:
     pass
@@ -184,20 +181,21 @@ def copy_op_to_graph(org_instance, to_graph, variables,
 
     #If it has an original_op parameter, copy it
     if op._original_op is not None:
-      new_original_op = copy_op_to_graph(op._original_op, to_graph,
-                                      variables, scope)
+      new_original_op = copy_op_to_graph(op._original_op, to_graph, variables,
+                                         scope)
     else:
       new_original_op = None
 
     #If it has control inputs, call this function recursively on each.
-    new_control_inputs = [copy_op_to_graph(x, to_graph, variables,
-                                        scope)
-                          for x in op.control_inputs]
+    new_control_inputs = [
+        copy_op_to_graph(x, to_graph, variables, scope)
+        for x in op.control_inputs
+    ]
 
     #If it has inputs, call this function recursively on each.
-    new_inputs = [copy_op_to_graph(x, to_graph, variables,
-                                scope)
-                  for x in op.inputs]
+    new_inputs = [
+        copy_op_to_graph(x, to_graph, variables, scope) for x in op.inputs
+    ]
 
     #Make a new node_def based on that of the original.
     #An instance of tensorflow.core.framework.node_def_pb2.NodeDef, it
@@ -216,13 +214,8 @@ def copy_op_to_graph(org_instance, to_graph, variables,
     op_def = deepcopy(op._op_def)
 
     #Initialize a new Operation instance
-    new_op = ops.Operation(new_node_def,
-                           to_graph,
-                           new_inputs,
-                           output_types,
-                           new_control_inputs,
-                           input_types,
-                           new_original_op,
+    new_op = ops.Operation(new_node_def, to_graph, new_inputs, output_types,
+                           new_control_inputs, input_types, new_original_op,
                            op_def)
     #Use Graph's hidden methods to add the op
     to_graph._add_op(new_op)  # pylint: disable=protected-access
@@ -233,10 +226,10 @@ def copy_op_to_graph(org_instance, to_graph, variables,
     return new_op
 
   else:
-    raise TypeError("Could not copy instance: " + str(org_instance))
+    raise TypeError('Could not copy instance: ' + str(org_instance))
 
 
-def get_copied_op(org_instance, graph, scope=""):
+def get_copied_op(org_instance, graph, scope=''):
   """Given an `Operation` instance from some `Graph`, returns
   its namesake from `graph`, under the specified scope
   (default `""`).
@@ -259,5 +252,5 @@ def get_copied_op(org_instance, graph, scope=""):
   else:
     new_name = org_instance.name
 
-  return graph.as_graph_element(new_name, allow_tensor=True,
-                                allow_operation=True)
+  return graph.as_graph_element(
+      new_name, allow_tensor=True, allow_operation=True)