
'''simple docstring'''



import random
from typing import Any
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     list[Any]:




   """simple docstring"""
   for _ in range(len(SCREAMING_SNAKE_CASE_						)						):
      _SCREAMING_SNAKE_CASE          =				random.randint(0    ,      len(SCREAMING_SNAKE_CASE_						) - 1						)
      _SCREAMING_SNAKE_CASE          =				random.randint(0    ,      len(SCREAMING_SNAKE_CASE_						) - 1						)
      _SCREAMING_SNAKE_CASE     ,							_SCREAMING_SNAKE_CASE          =				data[b], data[a]
   return data


if __name__ == "__main__":
     UpperCamelCase__      :		str       							=  [0, 1, 2, 3, 4, 5, 6, 7]
     UpperCamelCase__      :		Optional[int]       							=  ["python", "says", "hello", "!"]
     print("Fisher-Yates Shuffle:")
     print("List", integers, strings)
     print("FY Shuffle", fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))








'''simple docstring'''



from typing import TYPE_CHECKING

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


UpperCamelCase__      :		str       							=  {
    "configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"],
    "tokenization_canine": ["CanineTokenizer"],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase__      :		List[Any]       							=  [
         "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

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






