




"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A_      			=       {
    '''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A_      			=       [
        '''MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''MegatronBertForCausalLM''',
        '''MegatronBertForMaskedLM''',
        '''MegatronBertForMultipleChoice''',
        '''MegatronBertForNextSentencePrediction''',
        '''MegatronBertForPreTraining''',
        '''MegatronBertForQuestionAnswering''',
        '''MegatronBertForSequenceClassification''',
        '''MegatronBertForTokenClassification''',
        '''MegatronBertModel''',
        '''MegatronBertPreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_megatron_bert import (
            MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            MegatronBertForCausalLM,
            MegatronBertForMaskedLM,
            MegatronBertForMultipleChoice,
            MegatronBertForNextSentencePrediction,
            MegatronBertForPreTraining,
            MegatronBertForQuestionAnswering,
            MegatronBertForSequenceClassification,
            MegatronBertForTokenClassification,
            MegatronBertModel,
            MegatronBertPreTrainedModel,
        )

else:
    import sys

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








"""simple docstring"""


from typing import Any


def       UpperCAmelCase__ (snake_case__							:      list					):
  """simple docstring"""

  if not input_list:
    return []
  _snake_case							:	List[Any]			=						[input_list.count(snake_case__					) for value in input_list]
  _snake_case							:	Optional[int]			=						max(snake_case__					)  # Gets the maximum count in the input list.
  # Gets values of modes
  return sorted({input_list[i] for i, value in enumerate(snake_case__					) if value == y}					)


if __name__ == "__main__":
     import doctest

     doctest.testmod()


