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# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Keyword args functions."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import functools
from tensorflow.python.util import decorator_utils
def keyword_args_only(func):
"""Decorator for marking specific function accepting keyword args only.
This decorator raises a `ValueError` if the input `func` is called with any
non-keyword args. This prevents the caller from providing the arguments in
wrong order.
Args:
func: The function or method needed to be decorated.
Returns:
Decorated function or method.
Raises:
ValueError: If `func` is not callable.
"""
decorator_utils.validate_callable(func, "keyword_args_only")
@functools.wraps(func)
def new_func(*args, **kwargs):
"""Keyword args only wrapper."""
if args:
raise ValueError(
"Must use keyword args to call {}.".format(func.__name__))
return func(**kwargs)
return new_func
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