



# Copyright 2023 The HuggingFace Team. 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.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


SCREAMING_SNAKE_CASE_:List[str]             =						{"""configuration_mra""": ["""MRA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MraConfig"""]}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE_:Tuple             =						[
         """MRA_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """MraForMaskedLM""",
         """MraForMultipleChoice""",
         """MraForQuestionAnswering""",
         """MraForSequenceClassification""",
         """MraForTokenClassification""",
         """MraLayer""",
         """MraModel""",
         """MraPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_mra import (
              MRA_PRETRAINED_MODEL_ARCHIVE_LIST,
              MraForMaskedLM,
              MraForMultipleChoice,
              MraForQuestionAnswering,
              MraForSequenceClassification,
              MraForTokenClassification,
              MraLayer,
              MraModel,
              MraPreTrainedModel,
          )
else:
     import sys

     SCREAMING_SNAKE_CASE_:List[Any]             =						_LazyModule(__name__, globals()["""__file__"""], _import_structure)







def 	__UpperCamelCase	(  _lowerCAmelCase      ,     _lowerCAmelCase		)       ->  int:



    """simple docstring"""






    while second != 0:
        A :       int          =   first & second
        first ^= second
        A :       Tuple          =   c << 1
    return first


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     SCREAMING_SNAKE_CASE_:int             =						int(input("""Enter the first number: """).strip())
     SCREAMING_SNAKE_CASE_:Optional[int]             =						int(input("""Enter the second number: """).strip())
     print(F"""{add(first, second) = }""")


