from typing import TYPE_CHECKING

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


_lowerCAmelCase       =		{
    "configuration_rembert": ["REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RemBertConfig", "RemBertOnnxConfig"]
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCAmelCase       =		["RemBertTokenizer"]

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCAmelCase       =		["RemBertTokenizerFast"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCAmelCase       =		[
					    "REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "RemBertForCausalLM",
					    "RemBertForMaskedLM",
					    "RemBertForMultipleChoice",
					    "RemBertForQuestionAnswering",
					    "RemBertForSequenceClassification",
					    "RemBertForTokenClassification",
					    "RemBertLayer",
					    "RemBertModel",
					    "RemBertPreTrainedModel",
					    "load_tf_weights_in_rembert",
					]


try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCAmelCase       =		[
					    "TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "TFRemBertForCausalLM",
					    "TFRemBertForMaskedLM",
					    "TFRemBertForMultipleChoice",
					    "TFRemBertForQuestionAnswering",
					    "TFRemBertForSequenceClassification",
					    "TFRemBertForTokenClassification",
					    "TFRemBertLayer",
					    "TFRemBertModel",
					    "TFRemBertPreTrainedModel",
					]


if TYPE_CHECKING:
					from .configuration_rembert import REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RemBertConfig, RemBertOnnxConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_rembert import RemBertTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_rembert_fast import RemBertTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_rembert import (
										    REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    RemBertForCausalLM,
										    RemBertForMaskedLM,
										    RemBertForMultipleChoice,
										    RemBertForQuestionAnswering,
										    RemBertForSequenceClassification,
										    RemBertForTokenClassification,
										    RemBertLayer,
										    RemBertModel,
										    RemBertPreTrainedModel,
										    load_tf_weights_in_rembert,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_rembert import (
										    TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFRemBertForCausalLM,
										    TFRemBertForMaskedLM,
										    TFRemBertForMultipleChoice,
										    TFRemBertForQuestionAnswering,
										    TFRemBertForSequenceClassification,
										    TFRemBertForTokenClassification,
										    TFRemBertLayer,
										    TFRemBertModel,
										    TFRemBertPreTrainedModel,
										)


else:
					import sys

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




def 							__lowerCamelCase		(					UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						int		):




      """simple docstring"""





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




      """simple docstring"""





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


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





