"""simple docstring"""


def 					__a   (		A    ,				A      ):






					'''simple docstring'''



					if b == 0:
										return 1
					if (b % 2) == 0:
										return actual_power(A    ,				int(b / 2      )      ) * actual_power(A    ,				int(b / 2      )      )
					else:
										return a * actual_power(A    ,				int(b / 2      )      ) * actual_power(A    ,				int(b / 2      )      )







def 					__a   (		A    ,				A      ):






					'''simple docstring'''



					if b < 0:
										return 1 / actual_power(A    ,				A      )
					return actual_power(A    ,				A      )


if __name__ == "__main__":
	print(power(-2, -3))





"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase_:					Union[str, Any]     =					{
    "configuration_distilbert": [
        "DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "DistilBertConfig",
        "DistilBertOnnxConfig",
    ],
    "tokenization_distilbert": ["DistilBertTokenizer"],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_:					Union[str, Any]     =					["DistilBertTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_:					Any     =					[
     "DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "DistilBertForMaskedLM",
     "DistilBertForMultipleChoice",
     "DistilBertForQuestionAnswering",
     "DistilBertForSequenceClassification",
     "DistilBertForTokenClassification",
     "DistilBertModel",
     "DistilBertPreTrainedModel",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_:					Tuple     =					[
     "TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TFDistilBertForMaskedLM",
     "TFDistilBertForMultipleChoice",
     "TFDistilBertForQuestionAnswering",
     "TFDistilBertForSequenceClassification",
     "TFDistilBertForTokenClassification",
     "TFDistilBertMainLayer",
     "TFDistilBertModel",
     "TFDistilBertPreTrainedModel",
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_:					Optional[Any]     =					[
     "FlaxDistilBertForMaskedLM",
     "FlaxDistilBertForMultipleChoice",
     "FlaxDistilBertForQuestionAnswering",
     "FlaxDistilBertForSequenceClassification",
     "FlaxDistilBertForTokenClassification",
     "FlaxDistilBertModel",
     "FlaxDistilBertPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_distilbert import (
     DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
     DistilBertConfig,
     DistilBertOnnxConfig,
 )
 from .tokenization_distilbert import DistilBertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_distilbert_fast import DistilBertTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_distilbert import (
      DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      DistilBertForMaskedLM,
      DistilBertForMultipleChoice,
      DistilBertForQuestionAnswering,
      DistilBertForSequenceClassification,
      DistilBertForTokenClassification,
      DistilBertModel,
      DistilBertPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_distilbert import (
      TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFDistilBertForMaskedLM,
      TFDistilBertForMultipleChoice,
      TFDistilBertForQuestionAnswering,
      TFDistilBertForSequenceClassification,
      TFDistilBertForTokenClassification,
      TFDistilBertMainLayer,
      TFDistilBertModel,
      TFDistilBertPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_distilbert import (
      FlaxDistilBertForMaskedLM,
      FlaxDistilBertForMultipleChoice,
      FlaxDistilBertForQuestionAnswering,
      FlaxDistilBertForSequenceClassification,
      FlaxDistilBertForTokenClassification,
      FlaxDistilBertModel,
      FlaxDistilBertPreTrainedModel,
  )

else:
 import sys

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




