

from typing import TYPE_CHECKING

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


__lowercase				      =						{
    """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:
      __lowercase				      =						[
          """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

      __lowercase				      =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








def 							_lowerCamelCase   (			SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE   ):
      '''simple docstring'''







      A_							       =		len(SCREAMING_SNAKE_CASE   )
      A_							       =		len(SCREAMING_SNAKE_CASE   )
      A_							       =		(
          first_str_length if first_str_length > second_str_length else second_str_length
      )
      A_							       =		[]
      for char_count in range(SCREAMING_SNAKE_CASE   ):
            if char_count < first_str_length:
                  output_list.append(first_str[char_count]   )
            if char_count < second_str_length:
                  output_list.append(second_str[char_count]   )
      return "".join(SCREAMING_SNAKE_CASE   )


if __name__ == "__main__":
      print(alternative_string_arrange("""AB""", """XYZ"""), end=""" """)





