




'''simple docstring'''





from __future__ import annotations

import math




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase   ):
				__magic_name__	:	Dict								=u
				for i in range(1	,     _lowerCAmelCase   ):
								__magic_name__	:	Optional[Any]								=temp * (u - i)
				return temp




def 		lowerCAmelCase_   (	):
				__magic_name__	:	Optional[Any]								=int(input("""enter the numbers of values: """   )   )
				__magic_name__	:	list[list[float]]								=[]
				for _ in range(_lowerCAmelCase   ):
								y.append([]   )
				for i in range(_lowerCAmelCase   ):
								for j in range(_lowerCAmelCase   ):
												y[i].append(_lowerCAmelCase   )
												__magic_name__	:	str								=0

				print("""enter the values of parameters in a list: """   )
				__magic_name__	:	Tuple								=list(map(_lowerCAmelCase	,     input().split()   )   )

				print("""enter the values of corresponding parameters: """   )
				for i in range(_lowerCAmelCase   ):
								__magic_name__	:	Union[str, Any]								=float(input()   )

				__magic_name__	:	Optional[int]								=int(input("""enter the value to interpolate: """   )   )
				__magic_name__	:	int								=(value - x[0]) / (x[1] - x[0])

				# for calculating forward difference table

				for i in range(1	,     _lowerCAmelCase   ):
								for j in range(n - i   ):
												__magic_name__	:	Optional[Any]								=y[j + 1][i - 1] - y[j][i - 1]

				__magic_name__	:	int								=y[0][0]
				for i in range(1	,     _lowerCAmelCase   ):
								summ += (ucal(_lowerCAmelCase	,     _lowerCAmelCase   ) * y[0][i]) / math.factorial(_lowerCAmelCase   )

				print(F"the value at {value} is {summ}"   )


if __name__ == "__main__":
							main()










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_		:				Dict									=     {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_		:				Optional[int]									=     [
							    "WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "WavLMForAudioFrameClassification",
							    "WavLMForCTC",
							    "WavLMForSequenceClassification",
							    "WavLMForXVector",
							    "WavLMModel",
							    "WavLMPreTrainedModel",
							]

if TYPE_CHECKING:
							from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_wavlm import (
														    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    WavLMForAudioFrameClassification,
														    WavLMForCTC,
														    WavLMForSequenceClassification,
														    WavLMForXVector,
														    WavLMModel,
														    WavLMPreTrainedModel,
														)

else:
							import sys

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




