




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_UpperCAmelCase	:						List[Any]			=     {
    "configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
    "tokenization_roc_bert": ["RoCBertTokenizer"],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     pass

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase	:						List[Any]			=     [
         "ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "RoCBertForCausalLM",
         "RoCBertForMaskedLM",
         "RoCBertForMultipleChoice",
         "RoCBertForPreTraining",
         "RoCBertForQuestionAnswering",
         "RoCBertForSequenceClassification",
         "RoCBertForTokenClassification",
         "RoCBertLayer",
         "RoCBertModel",
         "RoCBertPreTrainedModel",
         "load_tf_weights_in_roc_bert",
     ]

if TYPE_CHECKING:
     from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
     from .tokenization_roc_bert import RoCBertTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          raise OptionalDependencyNotAvailable()

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_roc_bert import (
              ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              RoCBertForCausalLM,
              RoCBertForMaskedLM,
              RoCBertForMultipleChoice,
              RoCBertForPreTraining,
              RoCBertForQuestionAnswering,
              RoCBertForSequenceClassification,
              RoCBertForTokenClassification,
              RoCBertLayer,
              RoCBertModel,
              RoCBertPreTrainedModel,
              load_tf_weights_in_roc_bert,
          )


else:
     import sys

     _UpperCAmelCase	:						Union[str, Any]			=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)









def       UpperCAmelCase__  (     lowerCamelCase = "The quick brown fox jumps over the lazy dog",			):
  lowercase    :Dict      	=						set()

  # Replace all the whitespace in our sentence
  lowercase    :Optional[int]      	=						input_str.replace(" ",			""   )
  for alpha in input_str:
    if "a" <= alpha.lower() <= "z":
      frequency.add(alpha.lower()   )
  return len(lowerCamelCase   ) == 26



def       UpperCAmelCase__  (     lowerCamelCase = "The quick brown fox jumps over the lazy dog",			):
  lowercase    :Optional[Any]      	=						[False] * 26
  for char in input_str:
    if char.islower():
      lowercase    :Union[str, Any]      	=						True
    elif char.isupper():
      lowercase    :int      	=						True
  return all(lowerCamelCase   )



def       UpperCAmelCase__  (     lowerCamelCase = "The quick brown fox jumps over the lazy dog",			):
  return len({char for char in input_str.lower() if char.isalpha()}   ) == 26



def       UpperCAmelCase__  (     ):
  from timeit import timeit

  lowercase    :Optional[Any]      	=						"from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest"
  print(timeit("is_pangram()",			setup=lowerCamelCase   )   )
  print(timeit("is_pangram_faster()",			setup=lowerCamelCase   )   )
  print(timeit("is_pangram_fastest()",			setup=lowerCamelCase   )   )
  # 5.348480500048026, 2.6477354579837993, 1.8470395830227062
  # 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     benchmark()



