


"""simple docstring"""
from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE							:			Any						=			{
    """configuration_roberta""": ["""ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RobertaConfig""", """RobertaOnnxConfig"""],
    """tokenization_roberta""": ["""RobertaTokenizer"""],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE							:			Dict						=			["""RobertaTokenizerFast"""]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE							:			Optional[Any]						=			[
				    """ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """RobertaForCausalLM""",
				    """RobertaForMaskedLM""",
				    """RobertaForMultipleChoice""",
				    """RobertaForQuestionAnswering""",
				    """RobertaForSequenceClassification""",
				    """RobertaForTokenClassification""",
				    """RobertaModel""",
				    """RobertaPreTrainedModel""",
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE							:			Dict						=			[
				    """TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """TFRobertaForCausalLM""",
				    """TFRobertaForMaskedLM""",
				    """TFRobertaForMultipleChoice""",
				    """TFRobertaForQuestionAnswering""",
				    """TFRobertaForSequenceClassification""",
				    """TFRobertaForTokenClassification""",
				    """TFRobertaMainLayer""",
				    """TFRobertaModel""",
				    """TFRobertaPreTrainedModel""",
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE							:			List[str]						=			[
				    """FlaxRobertaForCausalLM""",
				    """FlaxRobertaForMaskedLM""",
				    """FlaxRobertaForMultipleChoice""",
				    """FlaxRobertaForQuestionAnswering""",
				    """FlaxRobertaForSequenceClassification""",
				    """FlaxRobertaForTokenClassification""",
				    """FlaxRobertaModel""",
				    """FlaxRobertaPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_roberta import ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, RobertaConfig, RobertaOnnxConfig
				from .tokenization_roberta import RobertaTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_roberta_fast import RobertaTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_roberta import (
								    ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
								    RobertaForCausalLM,
								    RobertaForMaskedLM,
								    RobertaForMultipleChoice,
								    RobertaForQuestionAnswering,
								    RobertaForSequenceClassification,
								    RobertaForTokenClassification,
								    RobertaModel,
								    RobertaPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_roberta import (
								    TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFRobertaForCausalLM,
								    TFRobertaForMaskedLM,
								    TFRobertaForMultipleChoice,
								    TFRobertaForQuestionAnswering,
								    TFRobertaForSequenceClassification,
								    TFRobertaForTokenClassification,
								    TFRobertaMainLayer,
								    TFRobertaModel,
								    TFRobertaPreTrainedModel,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_roberta import (
								    FlaxRobertaForCausalLM,
								    FlaxRobertaForMaskedLM,
								    FlaxRobertaForMultipleChoice,
								    FlaxRobertaForQuestionAnswering,
								    FlaxRobertaForSequenceClassification,
								    FlaxRobertaForTokenClassification,
								    FlaxRobertaModel,
								    FlaxRobertaPreTrainedModel,
								)

else:
				import sys

				__SCREAMING_SNAKE_CASE							:			List[str]						=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








'''simple docstring'''




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



def       __lowerCamelCase  (					_lowercase	,				_lowercase		)      ->			float:
							if b < 0:
														return 1 / actual_power(_lowercase	,				_lowercase		)
							return actual_power(_lowercase	,				_lowercase		)


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

