


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_   (	_a     ,       _a     ,       _a     ,       _a     ,       _a=True     ,       _a="pt"	):




		"""simple docstring"""






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






def 					lowerCamelCase_   (	_a     ,       _a     ,       _a=None     ,       ):




		"""simple docstring"""






		lowerCAmelCase__       :      Optional[int]   					= input_ids.ne(_a	).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  _a							(    _lowercase):




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




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




	def __getitem__( self						:		Union[str, Any]		, _SCREAMING_SNAKE_CASE						:		Optional[int]		)->	Dict[str, torch.Tensor]:
			lowerCAmelCase__       :      Any   					= index + 1  # linecache starts at 1
			lowerCAmelCase__       :      Dict   					= self.prefix + linecache.getline(str(self.src_file		)		, _SCREAMING_SNAKE_CASE		).rstrip('''\n'''		)
			lowerCAmelCase__       :      int   					= linecache.getline(str(self.tgt_file		)		, _SCREAMING_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		, _SCREAMING_SNAKE_CASE		):
					source_line += self.tokenizer.eos_token
					tgt_line += self.tokenizer.eos_token

			# Pad source and target to the right
			lowerCAmelCase__       :      Tuple   					= (
			    self.tokenizer.question_encoder if isinstance(self.tokenizer		, _SCREAMING_SNAKE_CASE		) else self.tokenizer
			)
			lowerCAmelCase__       :      Union[str, Any]   					= self.tokenizer.generator if isinstance(self.tokenizer		, _SCREAMING_SNAKE_CASE		) else self.tokenizer

			lowerCAmelCase__       :      int   					= encode_line(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, self.max_source_length		, '''right'''		)
			lowerCAmelCase__       :      Any   					= encode_line(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, self.max_target_length		, '''right'''		)

			lowerCAmelCase__       :      Dict   					= source_inputs['''input_ids'''].squeeze()
			lowerCAmelCase__       :      List[Any]   					= target_inputs['''input_ids'''].squeeze()
			lowerCAmelCase__       :      List[Any]   					= source_inputs['''attention_mask'''].squeeze()
			return {
			    "input_ids": source_ids,
			    "attention_mask": src_mask,
			    "decoder_input_ids": target_ids,
			}




	@staticmethod
	def 							UpperCAmelCase__( _SCREAMING_SNAKE_CASE						:		Dict		)->	int:
			return [len(_SCREAMING_SNAKE_CASE		) for x in Path(_SCREAMING_SNAKE_CASE		).open().readlines()]




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






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






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






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		lowerCAmelCase__       :      Dict   					= get_git_info()
		save_json(_a     ,       os.path.join(_a     ,       '''git_log.json'''	)	)






def 					lowerCamelCase_   (	_a     ,       _a     ,       _a=4     ,       **_a	):




		"""simple docstring"""






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






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






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






def 					lowerCamelCase_   (	):




		"""simple docstring"""






		lowerCAmelCase__       :      str   					= git.Repo(search_parent_directories=_a	)
		lowerCAmelCase__       :      Optional[int]   					= {
		    '''repo_id''': str(_a	),
		    '''repo_sha''': str(repo.head.object.hexsha	),
		    '''repo_branch''': str(repo.active_branch	),
		    '''hostname''': str(socket.gethostname()	),
		}
		return repo_infos






def 					lowerCamelCase_   (	_a     ,       _a	):




		"""simple docstring"""






		return list(map(_a     ,       _a	)	)






def 					lowerCamelCase_   (	_a     ,       _a	):




		"""simple docstring"""






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






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






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

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

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

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

		return white_space_fix(remove_articles(remove_punc(lower(_a	)	)	)	)






def 					lowerCamelCase_   (	_a     ,       _a	):




		"""simple docstring"""






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






def 					lowerCamelCase_   (	_a     ,       _a	):




		"""simple docstring"""






		return normalize_answer(_a	) == normalize_answer(_a	)






def 					lowerCamelCase_   (	_a     ,       _a	):




		"""simple docstring"""






		assert len(_a	) == len(_a	)
		lowerCAmelCase__       :      Optional[int]   					= 0
		for hypo, pred in zip(_a     ,       _a	):
				em += exact_match_score(_a     ,       _a	)
		if len(_a	) > 0:
				em /= len(_a	)
		return {"em": em}






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		return model_prefix.startswith('''rag'''	)






def 					lowerCamelCase_   (	_a     ,       _a     ,       _a	):




		"""simple docstring"""






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








def 					lowerCamelCase_   (	_a = 4_000_000	):




		"""simple docstring"""






		lowerCAmelCase__       :      str   					= []
		lowerCAmelCase__					,     lowerCAmelCase__       :      Optional[Any]   					= 0, 1
		while b <= n:
				if b % 2 == 0:
						even_fibs.append(_a	)
				lowerCAmelCase__					,     lowerCAmelCase__       :      Union[str, Any]   					= b, a + b
		return sum(_a	)


if __name__ == "__main__":
		print(f'''{solution() = }''')




