"""simple docstring"""







from typing import TYPE_CHECKING

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


UpperCamelCase_       :       Optional[int]							   =		{
    """configuration_dpr""": ["""DPR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPRConfig"""],
    """tokenization_dpr""": [
        """DPRContextEncoderTokenizer""",
        """DPRQuestionEncoderTokenizer""",
        """DPRReaderOutput""",
        """DPRReaderTokenizer""",
    ],
}


try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase_       :       Optional[Any]							   =		[
						    """DPRContextEncoderTokenizerFast""",
						    """DPRQuestionEncoderTokenizerFast""",
						    """DPRReaderTokenizerFast""",
						]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase_       :       Optional[Any]							   =		[
						    """DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """DPRContextEncoder""",
						    """DPRPretrainedContextEncoder""",
						    """DPRPreTrainedModel""",
						    """DPRPretrainedQuestionEncoder""",
						    """DPRPretrainedReader""",
						    """DPRQuestionEncoder""",
						    """DPRReader""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase_       :       Union[str, Any]							   =		[
						    """TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TFDPRContextEncoder""",
						    """TFDPRPretrainedContextEncoder""",
						    """TFDPRPretrainedQuestionEncoder""",
						    """TFDPRPretrainedReader""",
						    """TFDPRQuestionEncoder""",
						    """TFDPRReader""",
						]


if TYPE_CHECKING:
						from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
						from .tokenization_dpr import (
						    DPRContextEncoderTokenizer,
						    DPRQuestionEncoderTokenizer,
						    DPRReaderOutput,
						    DPRReaderTokenizer,
						)

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_dpr_fast import (
												    DPRContextEncoderTokenizerFast,
												    DPRQuestionEncoderTokenizerFast,
												    DPRReaderTokenizerFast,
												)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_dpr import (
												    DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DPRContextEncoder,
												    DPRPretrainedContextEncoder,
												    DPRPreTrainedModel,
												    DPRPretrainedQuestionEncoder,
												    DPRPretrainedReader,
												    DPRQuestionEncoder,
												    DPRReader,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_dpr import (
												    TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFDPRContextEncoder,
												    TFDPRPretrainedContextEncoder,
												    TFDPRPretrainedQuestionEncoder,
												    TFDPRPretrainedReader,
												    TFDPRQuestionEncoder,
												    TFDPRReader,
												)

else:
						import sys

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


"""simple docstring"""







from __future__ import annotations

import sys


def   a__      (		UpperCAmelCase__       :			int			)->	int:
						if n < 0:
												raise ValueError("""Negative arguments are not supported"""			)
						return _fib(UpperCAmelCase__			)[0]


def   a__      (		UpperCAmelCase__       :			int			)->	tuple[int, int]:
						if n == 0:  # (F(0), F(1))
												return (0, 1)

						# F(2n) = F(n)[2F(n+1) − F(n)]
						# F(2n+1) = F(n+1)^2+F(n)^2
						UpperCAmelCase__	,      UpperCAmelCase__						=		_fib(n // 2			)
						UpperCAmelCase__						=		a * (b * 2 - a)
						UpperCAmelCase__						=		a * a + b * b
						return (d, c + d) if n % 2 else (c, d)


if __name__ == "__main__":
						UpperCamelCase_       :       int							   =		int(sys.argv[1])
						print(F"""fibonacci({n}) is {fibonacci(n)}""")

