



# 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


UpperCAmelCase_		 =					{"""configuration_mra""": ["""MRA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MraConfig"""]}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase_		 =					[
       """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

   UpperCAmelCase_		 =					_LazyModule(__name__, globals()["""__file__"""], _import_structure)








def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:list				)  ->     bool:
   if not isinstance(_snake_case	,   _snake_case				):
      raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''				)
   if len(_snake_case				) == 0:
      raise ValueError('''Input list must be a non empty list'''				)
   if len(_snake_case				) == 1:
      return True
   _A      =       series[1] - series[0]
   for index in range(len(_snake_case				) - 1				):
      if series[index + 1] - series[index] != common_diff:
         return False
   return True

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:list				)  ->     float:
   if not isinstance(_snake_case	,   _snake_case				):
      raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''				)
   if len(_snake_case				) == 0:
      raise ValueError('''Input list must be a non empty list'''				)
   _A      =       0
   for val in series:
      answer += val
   return answer / len(_snake_case				)


if __name__ == "__main__":
   import doctest

   doctest.testmod()



