



from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE     =	{
    """configuration_xlm_prophetnet""": ["""XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMProphetNetConfig"""],
}

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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__SCREAMING_SNAKE_CASE     =	[
							    """XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """XLMProphetNetDecoder""",
							    """XLMProphetNetEncoder""",
							    """XLMProphetNetForCausalLM""",
							    """XLMProphetNetForConditionalGeneration""",
							    """XLMProphetNetModel""",
							    """XLMProphetNetPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_xlm_prophetnet import (
														    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
														    XLMProphetNetDecoder,
														    XLMProphetNetEncoder,
														    XLMProphetNetForCausalLM,
														    XLMProphetNetForConditionalGeneration,
														    XLMProphetNetModel,
														    XLMProphetNetPreTrainedModel,
														)

else:
							import sys

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




from collections.abc import Callable

__SCREAMING_SNAKE_CASE     =	Callable[[float], float]  # type alias for a real -> real function




def 						UpperCAmelCase (    _lowerCamelCase			,     _lowerCamelCase			,     _lowerCamelCase			,     ):
			A				:       int														=    float(_lowerCamelCase     )
			while True:
						try:
									A				:       Optional[int]														=    prev_guess - function(_lowerCamelCase     ) / derivative(_lowerCamelCase     )
						except ZeroDivisionError:
									raise ZeroDivisionError("Could not find root"     ) from None
						if abs(prev_guess - next_guess     ) < 10**-5:
									return next_guess
						A				:       Any														=    next_guess




def 						UpperCAmelCase (    _lowerCamelCase     ):
			return (x**3) - (2 * x) - 5




def 						UpperCAmelCase (    _lowerCamelCase     ):
			return 3 * (x**2) - 2


if __name__ == "__main__":
							print(newton(f, fa, 3))