




from __future__ import annotations

import math
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					u
			for i in range(1					,	SCREAMING_SNAKE_CASE   ):
						SCREAMING_SNAKE_CASE           =					temp * (u - i)
			return temp
def 					lowerCamelCase_    (    ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					int(input("""enter the numbers of values: """   )   )
			SCREAMING_SNAKE_CASE           =					[]
			for _ in range(SCREAMING_SNAKE_CASE   ):
						y.append([]   )
			for i in range(SCREAMING_SNAKE_CASE   ):
						for j in range(SCREAMING_SNAKE_CASE   ):
									y[i].append(SCREAMING_SNAKE_CASE   )
									SCREAMING_SNAKE_CASE           =					0

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

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

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

			# for calculating forward difference table

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

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

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


if __name__ == "__main__":
		main()












import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE=True					,	SCREAMING_SNAKE_CASE="pt"   ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					{"""add_prefix_space""": True} if isinstance(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ) and not line.startswith(""" """   ) else {}
			SCREAMING_SNAKE_CASE           =					padding_side
			return tokenizer(
			    [line]					,	max_length=SCREAMING_SNAKE_CASE					,	padding="""max_length""" if pad_to_max_length else None					,	truncation=SCREAMING_SNAKE_CASE					,	return_tensors=SCREAMING_SNAKE_CASE					,	add_special_tokens=SCREAMING_SNAKE_CASE					,	**SCREAMING_SNAKE_CASE					,	)
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE=None					,	):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					input_ids.ne(SCREAMING_SNAKE_CASE   ).any(dim=0   )
			if attention_mask is None:
						return input_ids[:, keep_column_mask]
			else:
						return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])




class 			UpperCAmelCase_      (   A       ):




							'''simple docstring'''



							def __init__(					self       :	Any       ,     a       :	int       ,     a       :	List[str]       ,     a       :	Dict       ,     a       :	List[Any]       ,     a       :	Optional[Any]="train"       ,     a       :	Tuple=None       ,     a       :	List[str]=None       ,     a       :	Optional[int]=None       ,     a       :	List[str]=""       ,     )			->					Optional[Any]:
										super().__init__()
										SCREAMING_SNAKE_CASE           =					Path(a			).joinpath(type_path + """.source"""			)
										SCREAMING_SNAKE_CASE           =					Path(a			).joinpath(type_path + """.target"""			)
										SCREAMING_SNAKE_CASE           =					self.get_char_lens(self.src_file			)
										SCREAMING_SNAKE_CASE           =					max_source_length
										SCREAMING_SNAKE_CASE           =					max_target_length
										assert min(self.src_lens			) > 0, f"""found empty line in {self.src_file}"""
										SCREAMING_SNAKE_CASE           =					tokenizer
										SCREAMING_SNAKE_CASE           =					prefix
										if n_obs is not None:
													SCREAMING_SNAKE_CASE           =					self.src_lens[:n_obs]
										SCREAMING_SNAKE_CASE           =					src_lang
										SCREAMING_SNAKE_CASE           =					tgt_lang





							def __len__(					self       :	Union[str, Any]			)			->					Dict:
										return len(self.src_lens			)





							def __getitem__(					self       :	Any       ,     a       :	Optional[int]			)			->					Dict[str, torch.Tensor]:
										SCREAMING_SNAKE_CASE           =					index + 1  # linecache starts at 1
										SCREAMING_SNAKE_CASE           =					self.prefix + linecache.getline(str(self.src_file			)       ,     a			).rstrip("""\n"""			)
										SCREAMING_SNAKE_CASE           =					linecache.getline(str(self.tgt_file			)       ,     a			).rstrip("""\n"""			)
										assert source_line, f"""empty source line for index {index}"""
										assert tgt_line, f"""empty tgt line for index {index}"""

										# Need to add eos token manually for T5
										if isinstance(self.tokenizer       ,     a			):
													source_line += self.tokenizer.eos_token
													tgt_line += self.tokenizer.eos_token

										# Pad source and target to the right
										SCREAMING_SNAKE_CASE           =					(
										    self.tokenizer.question_encoder if isinstance(self.tokenizer       ,     a			) else self.tokenizer
										)
										SCREAMING_SNAKE_CASE           =					self.tokenizer.generator if isinstance(self.tokenizer       ,     a			) else self.tokenizer

										SCREAMING_SNAKE_CASE           =					encode_line(a       ,     a       ,     self.max_source_length       ,     """right"""			)
										SCREAMING_SNAKE_CASE           =					encode_line(a       ,     a       ,     self.max_target_length       ,     """right"""			)

										SCREAMING_SNAKE_CASE           =					source_inputs["""input_ids"""].squeeze()
										SCREAMING_SNAKE_CASE           =					target_inputs["""input_ids"""].squeeze()
										SCREAMING_SNAKE_CASE           =					source_inputs["""attention_mask"""].squeeze()
										return {
										    "input_ids": source_ids,
										    "attention_mask": src_mask,
										    "decoder_input_ids": target_ids,
										}





							@staticmethod
							def    _UpperCAmelCase     (					a       :	Optional[int]			)			->					List[Any]:
										return [len(a			) for x in Path(a			).open().readlines()]







							def    _UpperCAmelCase     (					self       :	Optional[int]       ,     a       :	List[Any]			)			->					Dict[str, torch.Tensor]:
										SCREAMING_SNAKE_CASE           =					torch.stack([x["""input_ids"""] for x in batch]			)
										SCREAMING_SNAKE_CASE           =					torch.stack([x["""attention_mask"""] for x in batch]			)
										SCREAMING_SNAKE_CASE           =					torch.stack([x["""decoder_input_ids"""] for x in batch]			)
										SCREAMING_SNAKE_CASE           =					(
										    self.tokenizer.generator.pad_token_id
										    if isinstance(self.tokenizer       ,     a			)
										    else self.tokenizer.pad_token_id
										)
										SCREAMING_SNAKE_CASE           =					(
										    self.tokenizer.question_encoder.pad_token_id
										    if isinstance(self.tokenizer       ,     a			)
										    else self.tokenizer.pad_token_id
										)
										SCREAMING_SNAKE_CASE           =					trim_batch(a       ,     a			)
										SCREAMING_SNAKE_CASE     ,  SCREAMING_SNAKE_CASE           =					trim_batch(a       ,     a       ,     attention_mask=a			)
										SCREAMING_SNAKE_CASE           =					{
										    """input_ids""": source_ids,
										    """attention_mask""": source_mask,
										    """decoder_input_ids""": y,
										}
										return batch





__A						:							Tuple							=  getLogger(__name__)
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			return list(itertools.chain.from_iterable(SCREAMING_SNAKE_CASE   )   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					get_git_info()
			save_json(SCREAMING_SNAKE_CASE					,	os.path.join(SCREAMING_SNAKE_CASE					,	"""git_log.json"""   )   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE=4					,	**SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			with open(SCREAMING_SNAKE_CASE					,	"""w"""   ) as f:
						json.dump(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	indent=SCREAMING_SNAKE_CASE					,	**SCREAMING_SNAKE_CASE   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			with open(SCREAMING_SNAKE_CASE   ) as f:
						return json.load(SCREAMING_SNAKE_CASE   )
def 					lowerCamelCase_    (    ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					git.Repo(search_parent_directories=SCREAMING_SNAKE_CASE   )
			SCREAMING_SNAKE_CASE           =					{
			    """repo_id""": str(SCREAMING_SNAKE_CASE   ),
			    """repo_sha""": str(repo.head.object.hexsha   ),
			    """repo_branch""": str(repo.active_branch   ),
			    """hostname""": str(socket.gethostname()   ),
			}
			return repo_infos
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			return list(map(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   )   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			with open(SCREAMING_SNAKE_CASE					,	"""wb"""   ) as f:
						return pickle.dump(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''

			def remove_articles(SCREAMING_SNAKE_CASE   ):
						return re.sub(r"""\b(a|an|the)\b"""					,	""" """					,	SCREAMING_SNAKE_CASE   )

			def white_space_fix(SCREAMING_SNAKE_CASE   ):
						return " ".join(text.split()   )

			def remove_punc(SCREAMING_SNAKE_CASE   ):
						SCREAMING_SNAKE_CASE           =					set(string.punctuation   )
						return "".join(ch for ch in text if ch not in exclude   )

			def lower(SCREAMING_SNAKE_CASE   ):
						return text.lower()

			return white_space_fix(remove_articles(remove_punc(lower(SCREAMING_SNAKE_CASE   )   )   )   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					normalize_answer(SCREAMING_SNAKE_CASE   ).split()
			SCREAMING_SNAKE_CASE           =					normalize_answer(SCREAMING_SNAKE_CASE   ).split()
			SCREAMING_SNAKE_CASE           =					Counter(SCREAMING_SNAKE_CASE   ) & Counter(SCREAMING_SNAKE_CASE   )
			SCREAMING_SNAKE_CASE           =					sum(common.values()   )
			if num_same == 0:
						return 0
			SCREAMING_SNAKE_CASE           =					1.0 * num_same / len(SCREAMING_SNAKE_CASE   )
			SCREAMING_SNAKE_CASE           =					1.0 * num_same / len(SCREAMING_SNAKE_CASE   )
			SCREAMING_SNAKE_CASE           =					(2 * precision * recall) / (precision + recall)
			return fa
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			return normalize_answer(SCREAMING_SNAKE_CASE   ) == normalize_answer(SCREAMING_SNAKE_CASE   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			assert len(SCREAMING_SNAKE_CASE   ) == len(SCREAMING_SNAKE_CASE   )
			SCREAMING_SNAKE_CASE           =					0
			for hypo, pred in zip(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
						em += exact_match_score(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   )
			if len(SCREAMING_SNAKE_CASE   ) > 0:
						em /= len(SCREAMING_SNAKE_CASE   )
			return {"em": em}
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			return model_prefix.startswith("""rag"""   )




def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					{p: p for p in extra_params}
			# T5 models don't have `dropout` param, they have `dropout_rate` instead
			SCREAMING_SNAKE_CASE           =					"""dropout_rate"""
			for p in extra_params:
						if getattr(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
									if not hasattr(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ) and not hasattr(SCREAMING_SNAKE_CASE					,	equivalent_param[p]   ):
												logger.info("""config doesn't have a `{}` attribute""".format(SCREAMING_SNAKE_CASE   )   )
												delattr(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   )
												continue
									SCREAMING_SNAKE_CASE           =					p if hasattr(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ) else equivalent_param[p]
									setattr(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	getattr(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   )   )
									delattr(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   )
			return hparams, config






