from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase      			=     {
    'configuration_big_bird': ['BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BigBirdConfig', 'BigBirdOnnxConfig'],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase      			=     ['BigBirdTokenizer']

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase      			=     ['BigBirdTokenizerFast']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase      			=     [
         'BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST',
         'BigBirdForCausalLM',
         'BigBirdForMaskedLM',
         'BigBirdForMultipleChoice',
         'BigBirdForPreTraining',
         'BigBirdForQuestionAnswering',
         'BigBirdForSequenceClassification',
         'BigBirdForTokenClassification',
         'BigBirdLayer',
         'BigBirdModel',
         'BigBirdPreTrainedModel',
         'load_tf_weights_in_big_bird',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase      			=     [
         'FlaxBigBirdForCausalLM',
         'FlaxBigBirdForMaskedLM',
         'FlaxBigBirdForMultipleChoice',
         'FlaxBigBirdForPreTraining',
         'FlaxBigBirdForQuestionAnswering',
         'FlaxBigBirdForSequenceClassification',
         'FlaxBigBirdForTokenClassification',
         'FlaxBigBirdModel',
         'FlaxBigBirdPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_big_bird import BigBirdTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_big_bird_fast import BigBirdTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_big_bird import (
              BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
              BigBirdForCausalLM,
              BigBirdForMaskedLM,
              BigBirdForMultipleChoice,
              BigBirdForPreTraining,
              BigBirdForQuestionAnswering,
              BigBirdForSequenceClassification,
              BigBirdForTokenClassification,
              BigBirdLayer,
              BigBirdModel,
              BigBirdPreTrainedModel,
              load_tf_weights_in_big_bird,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_big_bird import (
              FlaxBigBirdForCausalLM,
              FlaxBigBirdForMaskedLM,
              FlaxBigBirdForMultipleChoice,
              FlaxBigBirdForPreTraining,
              FlaxBigBirdForQuestionAnswering,
              FlaxBigBirdForSequenceClassification,
              FlaxBigBirdForTokenClassification,
              FlaxBigBirdModel,
              FlaxBigBirdPreTrainedModel,
          )

else:
     import sys

     UpperCamelCase      			=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






import os



def    lowerCamelCase_   (  )							->	List[str]:
		__A							:   Any	  =				0
		__A							:   Any	  =				0
		with open(os.path.dirname(_lowercase    ) + "/p022_names.txt"    ) as file:
				__A							:   int	  =				str(file.readlines()[0]    )
				__A							:   Optional[Any]	  =				name.replace("\"" ,     ""    ).split(","    )

		name.sort()
		for i in range(len(_lowercase    )    ):
				for j in name[i]:
						temp_sum += ord(_lowercase    ) - ord("A"    ) + 1
				total_sum += (i + 1) * temp_sum
				__A							:   List[Any]	  =				0
		return total_sum


if __name__ == "__main__":
					print(solution())





