
'''simple docstring'''




import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union

import torch

from ..utils import BaseOutput


lowercase     :							Optional[int]       						=     'scheduler_config.json'





class 					A							(				__snake_case		):
     __magic_name__          =						1
     __magic_name__          =						2
     __magic_name__          =						3
     __magic_name__          =						4
     __magic_name__          =						5
     __magic_name__          =						6
     __magic_name__          =						7
     __magic_name__          =						8
     __magic_name__          =						9
     __magic_name__          =						10
     __magic_name__          =						11
     __magic_name__          =						12
     __magic_name__          =						13
     __magic_name__          =						14





@dataclass
class 					A							(				__snake_case		):
     __magic_name__          =						42





class 					A							:
     __magic_name__          =						SCHEDULER_CONFIG_NAME
     __magic_name__          =						[]
     __magic_name__          =						True





     @classmethod
     def 							__lowerCAmelCase				(				cls		,     SCREAMING_SNAKE_CASE = None		,     SCREAMING_SNAKE_CASE = None		,     SCREAMING_SNAKE_CASE=False		,     **SCREAMING_SNAKE_CASE		,     )					->							Optional[Any]:






         """simple docstring"""






         A,    A,    A			:  str   =		cls.load_config(
             pretrained_model_name_or_path=SCREAMING_SNAKE_CASE		,     subfolder=SCREAMING_SNAKE_CASE		,     return_unused_kwargs=SCREAMING_SNAKE_CASE		,     return_commit_hash=SCREAMING_SNAKE_CASE		,     **SCREAMING_SNAKE_CASE		,     )
         return cls.from_config(SCREAMING_SNAKE_CASE		,     return_unused_kwargs=SCREAMING_SNAKE_CASE		,     **SCREAMING_SNAKE_CASE      )





     def 							__lowerCAmelCase				(				self		,     SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE = False		,     **SCREAMING_SNAKE_CASE      )					->							str:






         """simple docstring"""






         self.save_config(save_directory=SCREAMING_SNAKE_CASE		,     push_to_hub=SCREAMING_SNAKE_CASE		,     **SCREAMING_SNAKE_CASE      )





     @property
     def 							__lowerCAmelCase				(				self      )					->							Union[str, Any]:






         """simple docstring"""






         return self._get_compatibles()





     @classmethod
     def 							__lowerCAmelCase				(				cls      )					->							Tuple:






         """simple docstring"""






         A			:  Tuple   =		list(set([cls.__name__] + cls._compatibles      )      )
         A			:  Tuple   =		importlib.import_module(__name__.split('''.'''      )[0]      )
         A			:  Optional[int]   =		[
             getattr(SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE      ) for c in compatible_classes_str if hasattr(SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE      )
         ]
         return compatible_classes






'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase     :							Tuple       						=     {
    'configuration_luke': ['LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LukeConfig'],
    'tokenization_luke': ['LukeTokenizer'],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase     :							int       						=     [
          'LUKE_PRETRAINED_MODEL_ARCHIVE_LIST',
          'LukeForEntityClassification',
          'LukeForEntityPairClassification',
          'LukeForEntitySpanClassification',
          'LukeForMultipleChoice',
          'LukeForQuestionAnswering',
          'LukeForSequenceClassification',
          'LukeForTokenClassification',
          'LukeForMaskedLM',
          'LukeModel',
          'LukePreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
      from .tokenization_luke import LukeTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_luke import (
                LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
                LukeForEntityClassification,
                LukeForEntityPairClassification,
                LukeForEntitySpanClassification,
                LukeForMaskedLM,
                LukeForMultipleChoice,
                LukeForQuestionAnswering,
                LukeForSequenceClassification,
                LukeForTokenClassification,
                LukeModel,
                LukePreTrainedModel,
            )

else:
      import sys

      lowercase     :							Dict       						=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




