






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 					lowercase__				(					__snake_case   :							int					,	__snake_case   :							str					,	__snake_case   :							str					,	__snake_case   :							List[Any]					,	__snake_case   :							Optional[Any]=True					,	__snake_case   :							Dict="pt"  ):


					'''simple docstring'''


					UpperCAmelCase_   :				Dict						=						{'add_prefix_space': True} if isinstance(__snake_case					,	__snake_case  ) and not line.startswith(' '  ) else {}
					UpperCAmelCase_   :				List[Any]						=						padding_side
					return tokenizer(
					    [line]					,	max_length=__snake_case					,	padding='max_length' if pad_to_max_length else None					,	truncation=__snake_case					,	return_tensors=__snake_case					,	add_special_tokens=__snake_case					,	**__snake_case					,	)




def 					lowercase__				(					__snake_case   :							int					,	__snake_case   :							Any					,	__snake_case   :							Any=None					,	):


					'''simple docstring'''


					UpperCAmelCase_   :				Optional[int]						=						input_ids.ne(__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   lowerCamelCase				(_snake_case      ):







		'''simple docstring'''



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



		def __len__(							self       )     ->							List[str]:
							return len(self.src_lens       )



		def __getitem__(							self    ,		_UpperCamelCase       )     ->							Dict[str, torch.Tensor]:
							UpperCAmelCase_   :				Tuple						=						index + 1  # linecache starts at 1
							UpperCAmelCase_   :				Dict						=						self.prefix + linecache.getline(str(self.src_file       )    ,		_UpperCamelCase       ).rstrip('\n'       )
							UpperCAmelCase_   :				Tuple						=						linecache.getline(str(self.tgt_file       )    ,		_UpperCamelCase       ).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    ,		_UpperCamelCase       ):
												source_line += self.tokenizer.eos_token
												tgt_line += self.tokenizer.eos_token

							# Pad source and target to the right
							UpperCAmelCase_   :				str						=						(
							    self.tokenizer.question_encoder if isinstance(self.tokenizer    ,		_UpperCamelCase       ) else self.tokenizer
							)
							UpperCAmelCase_   :				Dict						=						self.tokenizer.generator if isinstance(self.tokenizer    ,		_UpperCamelCase       ) else self.tokenizer

							UpperCAmelCase_   :				Optional[int]						=						encode_line(_UpperCamelCase    ,		_UpperCamelCase    ,		self.max_source_length    ,		'right'       )
							UpperCAmelCase_   :				Dict						=						encode_line(_UpperCamelCase    ,		_UpperCamelCase    ,		self.max_target_length    ,		'right'       )

							UpperCAmelCase_   :				Union[str, Any]						=						source_inputs['input_ids'].squeeze()
							UpperCAmelCase_   :				str						=						target_inputs['input_ids'].squeeze()
							UpperCAmelCase_   :				int						=						source_inputs['attention_mask'].squeeze()
							return {
							    "input_ids": source_ids,
							    "attention_mask": src_mask,
							    "decoder_input_ids": target_ids,
							}



		@staticmethod
		def  __UpperCAmelCase      (							_UpperCamelCase       )     ->							Any:
							return [len(_UpperCamelCase       ) for x in Path(_UpperCamelCase       ).open().readlines()]



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





__UpperCAmelCase     							=						getLogger(__name__)




def 					lowercase__				(					__snake_case   :							List[List]  ):


					'''simple docstring'''


					return list(itertools.chain.from_iterable(__snake_case  )  )




def 					lowercase__				(					__snake_case   :							str  ):


					'''simple docstring'''


					UpperCAmelCase_   :				Optional[int]						=						get_git_info()
					save_json(__snake_case					,	os.path.join(__snake_case					,	'git_log.json'  )  )




def 					lowercase__				(					__snake_case   :							Union[str, Any]					,	__snake_case   :							List[Any]					,	__snake_case   :							Union[str, Any]=4					,	**__snake_case   :							Optional[Any]  ):


					'''simple docstring'''


					with open(__snake_case					,	'w'  ) as f:
										json.dump(__snake_case					,	__snake_case					,	indent=__snake_case					,	**__snake_case  )




def 					lowercase__				(					__snake_case   :							Union[str, Any]  ):


					'''simple docstring'''


					with open(__snake_case  ) as f:
										return json.load(__snake_case  )




def 					lowercase__				(					):


					'''simple docstring'''


					UpperCAmelCase_   :				str						=						git.Repo(search_parent_directories=__snake_case  )
					UpperCAmelCase_   :				str						=						{
					    'repo_id': str(__snake_case  ),
					    'repo_sha': str(repo.head.object.hexsha  ),
					    'repo_branch': str(repo.active_branch  ),
					    'hostname': str(socket.gethostname()  ),
					}
					return repo_infos




def 					lowercase__				(					__snake_case   :							Callable					,	__snake_case   :							Iterable  ):


					'''simple docstring'''


					return list(map(__snake_case					,	__snake_case  )  )




def 					lowercase__				(					__snake_case   :							str					,	__snake_case   :							str  ):


					'''simple docstring'''


					with open(__snake_case					,	'wb'  ) as f:
										return pickle.dump(__snake_case					,	__snake_case  )




def 					lowercase__				(					__snake_case   :							Dict  ):


					'''simple docstring'''


					def remove_articles(__snake_case   :							Any  ):
										return re.sub(R'\b(a|an|the)\b'					,	' '					,	__snake_case  )

					def white_space_fix(__snake_case   :							str  ):
										return " ".join(text.split()  )

					def remove_punc(__snake_case   :							List[str]  ):
										UpperCAmelCase_   :				Tuple						=						set(string.punctuation  )
										return "".join(ch for ch in text if ch not in exclude  )

					def lower(__snake_case   :							Union[str, Any]  ):
										return text.lower()

					return white_space_fix(remove_articles(remove_punc(lower(__snake_case  )  )  )  )




def 					lowercase__				(					__snake_case   :							List[str]					,	__snake_case   :							List[str]  ):


					'''simple docstring'''


					UpperCAmelCase_   :				Tuple						=						normalize_answer(__snake_case  ).split()
					UpperCAmelCase_   :				Union[str, Any]						=						normalize_answer(__snake_case  ).split()
					UpperCAmelCase_   :				List[str]						=						Counter(__snake_case  ) & Counter(__snake_case  )
					UpperCAmelCase_   :				str						=						sum(common.values()  )
					if num_same == 0:
										return 0
					UpperCAmelCase_   :				int						=						1.0 * num_same / len(__snake_case  )
					UpperCAmelCase_   :				List[Any]						=						1.0 * num_same / len(__snake_case  )
					UpperCAmelCase_   :				Optional[Any]						=						(2 * precision * recall) / (precision + recall)
					return fa




def 					lowercase__				(					__snake_case   :							Tuple					,	__snake_case   :							List[str]  ):


					'''simple docstring'''


					return normalize_answer(__snake_case  ) == normalize_answer(__snake_case  )




def 					lowercase__				(					__snake_case   :							List[str]					,	__snake_case   :							List[str]  ):


					'''simple docstring'''


					assert len(__snake_case  ) == len(__snake_case  )
					UpperCAmelCase_   :				int						=						0
					for hypo, pred in zip(__snake_case					,	__snake_case  ):
										em += exact_match_score(__snake_case					,	__snake_case  )
					if len(__snake_case  ) > 0:
										em /= len(__snake_case  )
					return {"em": em}




def 					lowercase__				(					__snake_case   :							Optional[int]  ):


					'''simple docstring'''


					return model_prefix.startswith('rag'  )






def 					lowercase__				(					__snake_case   :							int					,	__snake_case   :							Union[str, Any]					,	__snake_case   :							Any  ):


					'''simple docstring'''


					UpperCAmelCase_   :				int						=						{p: p for p in extra_params}
					# T5 models don't have `dropout` param, they have `dropout_rate` instead
					UpperCAmelCase_   :				Union[str, Any]						=						'dropout_rate'
					for p in extra_params:
										if getattr(__snake_case					,	__snake_case					,	__snake_case  ):
															if not hasattr(__snake_case					,	__snake_case  ) and not hasattr(__snake_case					,	equivalent_param[p]  ):
																				logger.info('config doesn\'t have a `{}` attribute'.format(__snake_case  )  )
																				delattr(__snake_case					,	__snake_case  )
																				continue
															UpperCAmelCase_   :				List[Any]						=						p if hasattr(__snake_case					,	__snake_case  ) else equivalent_param[p]
															setattr(__snake_case					,	__snake_case					,	getattr(__snake_case					,	__snake_case  )  )
															delattr(__snake_case					,	__snake_case  )
					return hparams, config














from __future__ import annotations




def 					lowercase__				(					__snake_case   :							list[int]					,	__snake_case   :							int  ):


					'''simple docstring'''


					if len(__snake_case  ) == 0:
										return False
					UpperCAmelCase_   :				Optional[int]						=						len(__snake_case  ) // 2
					if a_list[midpoint] == item:
										return True
					if item < a_list[midpoint]:
										return binary_search(a_list[:midpoint]					,	__snake_case  )
					else:
										return binary_search(a_list[midpoint + 1 :]					,	__snake_case  )


if __name__ == "__main__":
		__UpperCAmelCase     							=						input('Enter numbers separated by comma:\n').strip()
		__UpperCAmelCase     							=						[int(item.strip()) for item in user_input.split(',')]
		__UpperCAmelCase     							=						int(input('Enter the number to be found in the list:\n').strip())
		__UpperCAmelCase     							=						'' if binary_search(sequence, target) else 'not '
		print(F'{target} was {not_str}found in {sequence}')






