


'''simple docstring'''







def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       _lowerCAmelCase     :				List[Any]       =							len(_A       )
       _lowerCAmelCase     :				List[str]       =							[]
       for i in range(len(_A       ) - pat_len + 1       ):
              _lowerCAmelCase     :				Union[str, Any]       =							True
              for j in range(_A       ):
                     if s[i + j] != pattern[j]:
                            _lowerCAmelCase     :				Dict       =							False
                            break
              if match_found:
                     position.append(_A       )
       return position


if __name__ == "__main__":
       assert naive_pattern_search("""ABCDEFG""", """DE""") == [3]
       print(naive_pattern_search("""ABAAABCDBBABCDDEBCABC""", """ABC"""))





'''simple docstring'''







from typing import TYPE_CHECKING

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


lowerCAmelCase     :  Any											=    {
    """configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CanineConfig"""],
    """tokenization_canine""": ["""CanineTokenizer"""],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase     :  Tuple											=    [
           """CANINE_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """CanineForMultipleChoice""",
           """CanineForQuestionAnswering""",
           """CanineForSequenceClassification""",
           """CanineForTokenClassification""",
           """CanineLayer""",
           """CanineModel""",
           """CaninePreTrainedModel""",
           """load_tf_weights_in_canine""",
       ]


if TYPE_CHECKING:
       from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
       from .tokenization_canine import CanineTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_canine import (
                  CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  CanineForMultipleChoice,
                  CanineForQuestionAnswering,
                  CanineForSequenceClassification,
                  CanineForTokenClassification,
                  CanineLayer,
                  CanineModel,
                  CaninePreTrainedModel,
                  load_tf_weights_in_canine,
              )


else:
       import sys

       lowerCAmelCase     :  Optional[Any]											=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

