


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     (				__lowerCAmelCase							:       str      ,					__lowerCAmelCase							:       str      ,					__lowerCAmelCase							:       Any      ,					__lowerCAmelCase							:       Dict      ,					__lowerCAmelCase							:       int=True      ,					__lowerCAmelCase							:       str="pt"     ):
							a__    =  {'add_prefix_space': True} if isinstance(__lowerCAmelCase      ,					__lowerCAmelCase     ) and not line.startswith(' '     ) else {}
							a__    =  padding_side
							return tokenizer(
							    [line]      ,					max_length=__lowerCAmelCase      ,					padding='max_length' if pad_to_max_length else None      ,					truncation=__lowerCAmelCase      ,					return_tensors=__lowerCAmelCase      ,					add_special_tokens=__lowerCAmelCase      ,					**__lowerCAmelCase      ,					)






def 							__lowercase     (				__lowerCAmelCase							:       List[Any]      ,					__lowerCAmelCase							:       Optional[int]      ,					__lowerCAmelCase							:       Tuple=None      ,					):
							a__    =  input_ids.ne(__lowerCAmelCase     ).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  snake_case_     (lowerCamelCase_   ):
					def __init__(   self     :Dict    ,__snake_case     :Tuple    ,__snake_case     :Union[str, Any]    ,__snake_case     :Union[str, Any]    ,__snake_case     :Union[str, Any]    ,__snake_case     :Optional[Any]="train"    ,__snake_case     :str=None    ,__snake_case     :Optional[Any]=None    ,__snake_case     :List[Any]=None    ,__snake_case     :str=""    ,)      ->					Any:
												super().__init__()
												a__    =  Path(__snake_case   ).joinpath(type_path + '.source'   )
												a__    =  Path(__snake_case   ).joinpath(type_path + '.target'   )
												a__    =  self.get_char_lens(self.src_file   )
												a__    =  max_source_length
												a__    =  max_target_length
												assert min(self.src_lens   ) > 0, F'found empty line in {self.src_file}'
												a__    =  tokenizer
												a__    =  prefix
												if n_obs is not None:
																			a__    =  self.src_lens[:n_obs]
												a__    =  src_lang
												a__    =  tgt_lang
					def __len__(   self     :Optional[int]   )      ->					str:
												return len(self.src_lens   )
					def __getitem__(   self     :Optional[Any]    ,__snake_case     :int   )      ->					Dict[str, torch.Tensor]:
												a__    =  index + 1  # linecache starts at 1
												a__    =  self.prefix + linecache.getline(str(self.src_file   )    ,__snake_case   ).rstrip('\n'   )
												a__    =  linecache.getline(str(self.tgt_file   )    ,__snake_case   ).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    ,__snake_case   ):
																			source_line += self.tokenizer.eos_token
																			tgt_line += self.tokenizer.eos_token

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

												a__    =  encode_line(__snake_case    ,__snake_case    ,self.max_source_length    ,'right'   )
												a__    =  encode_line(__snake_case    ,__snake_case    ,self.max_target_length    ,'right'   )

												a__    =  source_inputs['input_ids'].squeeze()
												a__    =  target_inputs['input_ids'].squeeze()
												a__    =  source_inputs['attention_mask'].squeeze()
												return {
												    "input_ids": source_ids,
												    "attention_mask": src_mask,
												    "decoder_input_ids": target_ids,
												}
					@staticmethod
					def 				lowerCamelCase__(   __snake_case     :List[str]   )      ->					Dict:
												return [len(__snake_case   ) for x in Path(__snake_case   ).open().readlines()]



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





snake_case							: List[Any]      =   getLogger(__name__)






def 							__lowercase     (				__lowerCAmelCase							:       List[List]     ):
							return list(itertools.chain.from_iterable(__lowerCAmelCase     )     )






def 							__lowercase     (				__lowerCAmelCase							:       str     ):
							a__    =  get_git_info()
							save_json(__lowerCAmelCase      ,					os.path.join(__lowerCAmelCase      ,					'git_log.json'     )     )






def 							__lowercase     (				__lowerCAmelCase							:       Any      ,					__lowerCAmelCase							:       Tuple      ,					__lowerCAmelCase							:       str=4      ,					**__lowerCAmelCase							:       Dict     ):
							with open(__lowerCAmelCase      ,					'w'     ) as f:
														json.dump(__lowerCAmelCase      ,					__lowerCAmelCase      ,					indent=__lowerCAmelCase      ,					**__lowerCAmelCase     )






def 							__lowercase     (				__lowerCAmelCase							:       List[str]     ):
							with open(__lowerCAmelCase     ) as f:
														return json.load(__lowerCAmelCase     )






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






def 							__lowercase     (				__lowerCAmelCase							:       Callable      ,					__lowerCAmelCase							:       Iterable     ):
							return list(map(__lowerCAmelCase      ,					__lowerCAmelCase     )     )






def 							__lowercase     (				__lowerCAmelCase							:       str      ,					__lowerCAmelCase							:       List[Any]     ):
							with open(__lowerCAmelCase      ,					'wb'     ) as f:
														return pickle.dump(__lowerCAmelCase      ,					__lowerCAmelCase     )






def 							__lowercase     (				__lowerCAmelCase							:       Tuple     ):

							def remove_articles(__lowerCAmelCase							:       Optional[Any]     ):
														return re.sub(R'\b(a|an|the)\b'      ,					' '      ,					__lowerCAmelCase     )

							def white_space_fix(__lowerCAmelCase							:       Optional[Any]     ):
														return " ".join(text.split()     )

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

							def lower(__lowerCAmelCase							:       List[str]     ):
														return text.lower()

							return white_space_fix(remove_articles(remove_punc(lower(__lowerCAmelCase     )     )     )     )






def 							__lowercase     (				__lowerCAmelCase							:       Dict      ,					__lowerCAmelCase							:       str     ):
							a__    =  normalize_answer(__lowerCAmelCase     ).split()
							a__    =  normalize_answer(__lowerCAmelCase     ).split()
							a__    =  Counter(__lowerCAmelCase     ) & Counter(__lowerCAmelCase     )
							a__    =  sum(common.values()     )
							if num_same == 0:
														return 0
							a__    =  1.0 * num_same / len(__lowerCAmelCase     )
							a__    =  1.0 * num_same / len(__lowerCAmelCase     )
							a__    =  (2 * precision * recall) / (precision + recall)
							return fa






def 							__lowercase     (				__lowerCAmelCase							:       Tuple      ,					__lowerCAmelCase							:       List[str]     ):
							return normalize_answer(__lowerCAmelCase     ) == normalize_answer(__lowerCAmelCase     )






def 							__lowercase     (				__lowerCAmelCase							:       List[str]      ,					__lowerCAmelCase							:       List[str]     ):
							assert len(__lowerCAmelCase     ) == len(__lowerCAmelCase     )
							a__    =  0
							for hypo, pred in zip(__lowerCAmelCase      ,					__lowerCAmelCase     ):
														em += exact_match_score(__lowerCAmelCase      ,					__lowerCAmelCase     )
							if len(__lowerCAmelCase     ) > 0:
														em /= len(__lowerCAmelCase     )
							return {"em": em}






def 							__lowercase     (				__lowerCAmelCase							:       int     ):
							return model_prefix.startswith('rag'     )






def 							__lowercase     (				__lowerCAmelCase							:       Tuple      ,					__lowerCAmelCase							:       Dict      ,					__lowerCAmelCase							:       Optional[Any]     ):
							a__    =  {p: p for p in extra_params}
							# T5 models don't have `dropout` param, they have `dropout_rate` instead
							a__    =  'dropout_rate'
							for p in extra_params:
														if getattr(__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase     ):
																					if not hasattr(__lowerCAmelCase      ,					__lowerCAmelCase     ) and not hasattr(__lowerCAmelCase      ,					equivalent_param[p]     ):
																												logger.info('config doesn\'t have a `{}` attribute'.format(__lowerCAmelCase     )     )
																												delattr(__lowerCAmelCase      ,					__lowerCAmelCase     )
																												continue
																					a__    =  p if hasattr(__lowerCAmelCase      ,					__lowerCAmelCase     ) else equivalent_param[p]
																					setattr(__lowerCAmelCase      ,					__lowerCAmelCase      ,					getattr(__lowerCAmelCase      ,					__lowerCAmelCase     )     )
																					delattr(__lowerCAmelCase      ,					__lowerCAmelCase     )
							return hparams, config








import unittest

from knapsack import greedy_knapsack as kp







class  snake_case_     (unittest.TestCase   ):
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					Union[str, Any]:
												a__    =  [10, 20, 30, 40, 50, 60]
												a__    =  [2, 4, 6, 8, 10, 12]
												a__    =  1_00
												self.assertEqual(kp.calc_profit(__snake_case    ,__snake_case    ,__snake_case   )    ,2_10   )
					def 				lowerCamelCase__(   self     :str   )      ->					Optional[int]:
												self.assertRaisesRegex(__snake_case    ,'max_weight must greater than zero.'   )
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					int:
												self.assertRaisesRegex(__snake_case    ,'Weight can not be negative.'   )
					def 				lowerCamelCase__(   self     :str   )      ->					List[str]:
												self.assertRaisesRegex(__snake_case    ,'Profit can not be negative.'   )
					def 				lowerCamelCase__(   self     :str   )      ->					Optional[Any]:
												self.assertRaisesRegex(__snake_case    ,'max_weight must greater than zero.'   )



					def 				lowerCamelCase__(   self     :int   )      ->					List[Any]:
												self.assertRaisesRegex(
												    __snake_case    ,'The length of profit and weight must be same.'   )


if __name__ == "__main__":
						unittest.main()




