# 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)
from ..utils import DummyObject, requires_backends





class      lowerCAmelCase						(					metaclass=_a			):
     _SCREAMING_SNAKE_CASE     :     Optional[int]		=["""transformers""", """torch""", """note_seq"""]



     def __init__(					self				,      *lowerCAmelCase__				,      **lowerCAmelCase__       ):
            requires_backends(self				,      ['transformers', 'torch', 'note_seq']       )



     @classmethod
     def 			a__  (					cls				,      *lowerCAmelCase__				,      **lowerCAmelCase__       ):
            requires_backends(cls				,      ['transformers', 'torch', 'note_seq']       )





     @classmethod
     def 			a__  (					cls				,      *lowerCAmelCase__				,      **lowerCAmelCase__       ):
            requires_backends(cls				,      ['transformers', 'torch', 'note_seq']       )