From 3193ce82bb79fc9a737250ed7bc950d1dbee49da Mon Sep 17 00:00:00 2001 From: Srihari Humbarwadi Date: Mon, 18 Nov 2019 23:29:45 +0530 Subject: [PATCH] Update load.py --- tensorflow/python/saved_model/load.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/tensorflow/python/saved_model/load.py b/tensorflow/python/saved_model/load.py index b2ca7a4a257..4a44dd30e2f 100644 --- a/tensorflow/python/saved_model/load.py +++ b/tensorflow/python/saved_model/load.py @@ -50,10 +50,10 @@ from tensorflow.python.util.tf_export import tf_export def _unused_handle(): - """Returns a placeholder as handle that is not supposed to be accessed.""" + """Returns a placeholder as a handle that is not supposed to be accessed.""" error_message = ("Trying to access a placeholder that is not supposed to be " "executed. This means you are executing a graph generated " - "from cross-replica context in an in-replica context.") + "from the cross-replica context in an in-replica context.") assert_op = control_flow_ops.Assert( array_ops.placeholder_with_default(False, shape=()), @@ -76,7 +76,7 @@ class _WrapperFunction(function.ConcreteFunction): not in-replica, calling the function should mean that it is constructing a graph that is not actually going to be used. A typical use case is when constructing a functional model. In this case, return a placeholder with a - control dependency to ensure that is is never accessed. + control dependency to ensure that is never accessed. """ def __init__(self, concrete_function): @@ -344,7 +344,7 @@ class Loader(object): def _recreate_base_user_object(self, proto): del proto - # Note: each user object has its own class. This allows to make each one + # Note: each user object has its own class. This allows making each one # individually callable by adding a `__call__` method to the classes of # the objects instances that have a `__call__` property.