


from __future__ import annotations

import math


def 				lowerCamelCase__	(      a	:   Dict	,  a	:   Union[str, Any]				)    ->	List[str]:





			"""simple docstring"""
			a__ :List[str]						  =    u
			for i in range(1	,  UpperCamelCase__				):
						a__ :List[str]						  =    temp * (u - i)
			return temp


def 				lowerCamelCase__	(      )    ->	str:





			"""simple docstring"""
			a__ :int						  =    int(input("enter the numbers of values: "				)				)
			a__ :Tuple						  =    []
			for _ in range(UpperCamelCase__				):
						y.append([]				)
			for i in range(UpperCamelCase__				):
						for j in range(UpperCamelCase__				):
									y[i].append(UpperCamelCase__				)
									a__ :Optional[Any]						  =    0

			print("enter the values of parameters in a list: "				)
			a__ :int						  =    list(map(UpperCamelCase__	,  input().split()				)				)

			print("enter the values of corresponding parameters: "				)
			for i in range(UpperCamelCase__				):
						a__ :List[Any]						  =    float(input()				)

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

			# for calculating forward difference table

			for i in range(1	,  UpperCamelCase__				):
						for j in range(n - i				):
									a__ :Optional[int]						  =    y[j + 1][i - 1] - y[j][i - 1]

			a__ :Union[str, Any]						  =    y[0][0]
			for i in range(1	,  UpperCamelCase__				):
						summ += (ucal(UpperCamelCase__	,  UpperCamelCase__				) * y[0][i]) / math.factorial(UpperCamelCase__				)

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


if __name__ == "__main__":
		main()






# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case__			 =						{
    '''configuration_mgp_str''': ['''MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MgpstrConfig'''],
    '''processing_mgp_str''': ['''MgpstrProcessor'''],
    '''tokenization_mgp_str''': ['''MgpstrTokenizer'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		snake_case__			 =						[
		    '''MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''MgpstrModel''',
		    '''MgpstrPreTrainedModel''',
		    '''MgpstrForSceneTextRecognition''',
		]

if TYPE_CHECKING:
		from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
		from .processing_mgp_str import MgpstrProcessor
		from .tokenization_mgp_str import MgpstrTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mgp_str import (
				    MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MgpstrForSceneTextRecognition,
				    MgpstrModel,
				    MgpstrPreTrainedModel,
				)
else:
		import sys

		snake_case__			 =						_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


