


from __future__ import annotations

import math






def 			UpperCamelCase (     __magic_name__					:							float   ,   __magic_name__					:							int					)       ->  float:
		"""simple docstring"""




		lowercase__					      =		u
		for i in range(1   ,   __magic_name__					):
				lowercase__					      =		temp * (u - i)
		return temp






def 			UpperCamelCase (     )       ->  None:
		"""simple docstring"""




		lowercase__					      =		int(input("""enter the numbers of values: """					)					)
		lowercase__					      =		[]
		for _ in range(__magic_name__					):
				y.append([]					)
		for i in range(__magic_name__					):
				for j in range(__magic_name__					):
						y[i].append(__magic_name__					)
						lowercase__					      =		0

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

		print("""enter the values of corresponding parameters: """					)
		for i in range(__magic_name__					):
				lowercase__					      =		float(input()					)

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

		# for calculating forward difference table

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

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

		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, is_vision_available


A	:		Dict    =       {'configuration_glpn': ['GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GLPNConfig']}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A	:		Tuple    =       ['GLPNFeatureExtractor']
	A	:		List[str]    =       ['GLPNImageProcessor']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A	:		Optional[int]    =       [
	    'GLPN_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'GLPNForDepthEstimation',
	    'GLPNLayer',
	    'GLPNModel',
	    'GLPNPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_glpn import GLPNFeatureExtractor
		from .image_processing_glpn import GLPNImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_glpn import (
		    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GLPNForDepthEstimation,
		    GLPNLayer,
		    GLPNModel,
		    GLPNPreTrainedModel,
		)


else:
	import sys

	A	:		Tuple    =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

