




import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
					from transformers.pipelines.conversational import Conversation

__lowerCamelCase   :						List[Any]				=			logging.get_logger(__name__)


__lowerCamelCase   :						Union[str, Any]				=			{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

__lowerCamelCase   :						Tuple				=			{
    '''vocab_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json'''},
    '''merges_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt'''},
    '''tokenizer_config_file''': {
        '''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json'''
    },
}

__lowerCamelCase   :						Union[str, Any]				=			{'''facebook/blenderbot-3B''': 1_28}







@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 		lowercase__   (		):





					'''simple docstring'''






					__magic_name__							:	Dict    							=							(
					    list(range(ord('''!'''				)							,ord('''~'''				) + 1				)				) + list(range(ord('''¡'''				)							,ord('''¬'''				) + 1				)				) + list(range(ord('''®'''				)							,ord('''ÿ'''				) + 1				)				)
					)
					__magic_name__							:	Optional[Any]    							=							bs[:]
					__magic_name__							:	Tuple    							=							0
					for b in range(2**8				):
										if b not in bs:
															bs.append(_SCREAMING_SNAKE_CASE				)
															cs.append(2**8 + n				)
															n += 1
					__magic_name__							:	Any    							=							[chr(_SCREAMING_SNAKE_CASE				) for n in cs]
					return dict(zip(_SCREAMING_SNAKE_CASE							,_SCREAMING_SNAKE_CASE				)				)







def 		lowercase__   (		__A:	int				):





					'''simple docstring'''






					__magic_name__							:	Optional[int]    							=							set()
					__magic_name__							:	Any    							=							word[0]
					for char in word[1:]:
										pairs.add((prev_char, char)				)
										__magic_name__							:	Union[str, Any]    							=							char
					return pairs


class    lowerCamelCase    (		_lowerCamelCase						):






			'''simple docstring'''





			UpperCamelCase__								=VOCAB_FILES_NAMES
			UpperCamelCase__								=PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase__								=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase__								=['input_ids', 'attention_mask']

			def __init__( self			:   Union[str, Any]       ,						lowerCamelCase_			:   Optional[Any]       ,						lowerCamelCase_			:   Optional[Any]       ,						lowerCamelCase_			:   str="replace"       ,						lowerCamelCase_			:   Tuple="<s>"       ,						lowerCamelCase_			:   int="</s>"       ,						lowerCamelCase_			:   Tuple="</s>"       ,						lowerCamelCase_			:   Optional[Any]="<s>"       ,						lowerCamelCase_			:   Dict="<unk>"       ,						lowerCamelCase_			:   List[Any]="<pad>"       ,						lowerCamelCase_			:   Optional[Any]="<mask>"       ,						lowerCamelCase_			:   Tuple=False       ,						**lowerCamelCase_			:   Dict       ,						)						->   Any:
								__magic_name__							:	List[str]    							=							AddedToken(lowerCamelCase_       ,						lstrip=lowerCamelCase_       ,						rstrip=lowerCamelCase_  ) if isinstance(lowerCamelCase_       ,						lowerCamelCase_  ) else bos_token
								__magic_name__							:	Optional[int]    							=							AddedToken(lowerCamelCase_       ,						lstrip=lowerCamelCase_       ,						rstrip=lowerCamelCase_  ) if isinstance(lowerCamelCase_       ,						lowerCamelCase_  ) else eos_token
								__magic_name__							:	str    							=							AddedToken(lowerCamelCase_       ,						lstrip=lowerCamelCase_       ,						rstrip=lowerCamelCase_  ) if isinstance(lowerCamelCase_       ,						lowerCamelCase_  ) else sep_token
								__magic_name__							:	int    							=							AddedToken(lowerCamelCase_       ,						lstrip=lowerCamelCase_       ,						rstrip=lowerCamelCase_  ) if isinstance(lowerCamelCase_       ,						lowerCamelCase_  ) else cls_token
								__magic_name__							:	Union[str, Any]    							=							AddedToken(lowerCamelCase_       ,						lstrip=lowerCamelCase_       ,						rstrip=lowerCamelCase_  ) if isinstance(lowerCamelCase_       ,						lowerCamelCase_  ) else unk_token
								__magic_name__							:	Dict    							=							AddedToken(lowerCamelCase_       ,						lstrip=lowerCamelCase_       ,						rstrip=lowerCamelCase_  ) if isinstance(lowerCamelCase_       ,						lowerCamelCase_  ) else pad_token

								# Mask token behave like a normal word, i.e. include the space before it
								__magic_name__							:	List[str]    							=							AddedToken(lowerCamelCase_       ,						lstrip=lowerCamelCase_       ,						rstrip=lowerCamelCase_  ) if isinstance(lowerCamelCase_       ,						lowerCamelCase_  ) else mask_token

								super().__init__(
								    errors=lowerCamelCase_       ,						bos_token=lowerCamelCase_       ,						eos_token=lowerCamelCase_       ,						unk_token=lowerCamelCase_       ,						sep_token=lowerCamelCase_       ,						cls_token=lowerCamelCase_       ,						pad_token=lowerCamelCase_       ,						mask_token=lowerCamelCase_       ,						add_prefix_space=lowerCamelCase_       ,						**lowerCamelCase_       ,						)

								with open(lowerCamelCase_       ,						encoding='''utf-8'''  ) as vocab_handle:
													__magic_name__							:	List[str]    							=							json.load(lowerCamelCase_  )
								__magic_name__							:	Union[str, Any]    							=							{v: k for k, v in self.encoder.items()}
								__magic_name__							:	Union[str, Any]    							=							errors  # how to handle errors in decoding
								__magic_name__							:	int    							=							bytes_to_unicode()
								__magic_name__							:	List[Any]    							=							{v: k for k, v in self.byte_encoder.items()}
								with open(lowerCamelCase_       ,						encoding='''utf-8'''  ) as merges_handle:
													__magic_name__							:	Optional[int]    							=							merges_handle.read().split('''\n'''  )[1:-1]
								__magic_name__							:	Tuple    							=							[tuple(merge.split()  ) for merge in bpe_merges]
								__magic_name__							:	List[str]    							=							dict(zip(lowerCamelCase_       ,						range(len(lowerCamelCase_  )  )  )  )
								__magic_name__							:	Any    							=							{}
								__magic_name__							:	str    							=							add_prefix_space

								# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
								__magic_name__							:	str    							=							re.compile(R'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''  )

			@property
			# Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
			def 							UpperCAmelCase__       ( self			:   List[Any]  )						->   Union[str, Any]:
								return len(self.encoder  )

			def 							UpperCAmelCase__       ( self			:   Dict  )						->   Union[str, Any]:
								return dict(self.encoder       ,						**self.added_tokens_encoder  )

			def 							UpperCAmelCase__       ( self			:   Union[str, Any]       ,						lowerCamelCase_			:   List[str]  )						->   Any:







								if token in self.cache:
													return self.cache[token]
								__magic_name__							:	Union[str, Any]    							=							tuple(lowerCamelCase_  )
								__magic_name__							:	int    							=							get_pairs(lowerCamelCase_  )

								if not pairs:
													return token

								while True:
													__magic_name__							:	Dict    							=							min(lowerCamelCase_       ,						key=lambda lowerCamelCase_  : self.bpe_ranks.get(lowerCamelCase_       ,						float('''inf'''  )  )  )
													if bigram not in self.bpe_ranks:
																		break
													__magic_name__							,    __magic_name__							:	Optional[Any]    							=							bigram
													__magic_name__							:	List[str]    							=							[]
													__magic_name__							:	List[str]    							=							0
													while i < len(lowerCamelCase_  ):
																		try:
																							__magic_name__							:	List[str]    							=							word.index(lowerCamelCase_       ,						lowerCamelCase_  )
																		except ValueError:
																							new_word.extend(word[i:]  )
																							break
																		else:
																							new_word.extend(word[i:j]  )
																							__magic_name__							:	Optional[int]    							=							j

																		if word[i] == first and i < len(lowerCamelCase_  ) - 1 and word[i + 1] == second:
																							new_word.append(first + second  )
																							i += 2
																		else:
																							new_word.append(word[i]  )
																							i += 1
													__magic_name__							:	Optional[int]    							=							tuple(lowerCamelCase_  )
													__magic_name__							:	Any    							=							new_word
													if len(lowerCamelCase_  ) == 1:
																		break
													else:
																		__magic_name__							:	int    							=							get_pairs(lowerCamelCase_  )
								__magic_name__							:	Optional[int]    							=							''' '''.join(lowerCamelCase_  )
								__magic_name__							:	str    							=							word
								return word

			def 							UpperCAmelCase__       ( self			:   List[Any]       ,						lowerCamelCase_			:   Any  )						->   Tuple:
								__magic_name__							:	str    							=							[]
								for token in re.findall(self.pat       ,						lowerCamelCase_  ):
													__magic_name__							:	int    							=							''''''.join(
													    self.byte_encoder[b] for b in token.encode('''utf-8'''  )  )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
													bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCamelCase_  ).split(''' '''  )  )
								return bpe_tokens

			def 							UpperCAmelCase__       ( self			:   Tuple       ,						lowerCamelCase_			:   Optional[int]  )						->   List[str]:
								return self.encoder.get(lowerCamelCase_       ,						self.encoder.get(self.unk_token  )  )

			def 							UpperCAmelCase__       ( self			:   Optional[int]       ,						lowerCamelCase_			:   int  )						->   int:
								return self.decoder.get(lowerCamelCase_  )

			def 							UpperCAmelCase__       ( self			:   Union[str, Any]       ,						lowerCamelCase_			:   Any  )						->   List[str]:
								__magic_name__							:	List[str]    							=							''''''.join(lowerCamelCase_  )
								__magic_name__							:	Any    							=							bytearray([self.byte_decoder[c] for c in text]  ).decode('''utf-8'''       ,						errors=self.errors  )
								return text

			def 							UpperCAmelCase__       ( self			:   Tuple       ,						lowerCamelCase_			:   str       ,						lowerCamelCase_			:   Optional[str] = None  )						->   Tuple[str]:







								if not os.path.isdir(lowerCamelCase_  ):
													logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
													return
								__magic_name__							:	int    							=							os.path.join(
								    lowerCamelCase_       ,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )
								__magic_name__							:	str    							=							os.path.join(
								    lowerCamelCase_       ,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']  )

								with open(lowerCamelCase_       ,						'''w'''       ,						encoding='''utf-8'''  ) as f:
													f.write(json.dumps(self.encoder       ,						indent=2       ,						sort_keys=lowerCamelCase_       ,						ensure_ascii=lowerCamelCase_  ) + '''\n'''  )

								__magic_name__							:	Optional[Any]    							=							0
								with open(lowerCamelCase_       ,						'''w'''       ,						encoding='''utf-8'''  ) as writer:
													writer.write('''#version: 0.2\n'''  )
													for bpe_tokens, token_index in sorted(self.bpe_ranks.items()       ,						key=lambda lowerCamelCase_  : kv[1]  ):
																		if index != token_index:
																							logger.warning(
																							    F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
																							    ''' Please check that the tokenizer is not corrupted!'''  )
																							__magic_name__							:	List[str]    							=							token_index
																		writer.write(''' '''.join(lowerCamelCase_  ) + '''\n'''  )
																		index += 1

								return vocab_file, merge_file

			def 							UpperCAmelCase__       ( self			:   Optional[int]       ,						lowerCamelCase_			:   List[int]       ,						lowerCamelCase_			:   Optional[List[int]] = None       ,						lowerCamelCase_			:   bool = False  )						->   List[int]:







								if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=lowerCamelCase_       ,						token_ids_a=lowerCamelCase_       ,						already_has_special_tokens=lowerCamelCase_  )

								if token_ids_a is None:
													return [1] + ([0] * len(lowerCamelCase_  )) + [1]
								return [1] + ([0] * len(lowerCamelCase_  )) + [1, 1] + ([0] * len(lowerCamelCase_  )) + [1]

			def 							UpperCAmelCase__       ( self			:   List[Any]       ,						lowerCamelCase_			:   List[int]       ,						lowerCamelCase_			:   Optional[List[int]] = None  )						->   List[int]:
								__magic_name__							:	int    							=							[self.sep_token_id]
								__magic_name__							:	Optional[int]    							=							[self.cls_token_id]

								if token_ids_a is None:
													return len(cls + token_ids_a + sep  ) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep  ) * [0]

			def 							UpperCAmelCase__       ( self			:   Union[str, Any]       ,						lowerCamelCase_			:   List[str]       ,						lowerCamelCase_			:   List[Any]=False       ,						**lowerCamelCase_			:   List[Any]  )						->   Union[str, Any]:
								__magic_name__							:	List[Any]    							=							kwargs.pop('''add_prefix_space'''       ,						self.add_prefix_space  )
								if (is_split_into_words or add_prefix_space) and (len(lowerCamelCase_  ) > 0 and not text[0].isspace()):
													__magic_name__							:	Tuple    							=							''' ''' + text
								return (text, kwargs)

			def 							UpperCAmelCase__       ( self			:   List[Any]       ,						lowerCamelCase_			:   List[int]       ,						lowerCamelCase_			:   Optional[List[int]] = None  )						->   Optional[Any]:
								return token_ids_a + [self.eos_token_id]


			def 							UpperCAmelCase__       ( self			:   Optional[Any]       ,						lowerCamelCase_			:   "Conversation"  )						->   List[int]:
								__magic_name__							:	List[Any]    							=							[]
								for is_user, text in conversation.iter_texts():
													if is_user:
																		# We need to space prefix as it's being done within blenderbot
																		inputs.append(''' ''' + text  )
													else:
																		# Generated responses should contain them already.
																		inputs.append(lowerCamelCase_  )

								__magic_name__							:	Tuple    							=							'''  '''.join(lowerCamelCase_  )
								__magic_name__							:	Any    							=							self.encode(lowerCamelCase_  )
								if len(lowerCamelCase_  ) > self.model_max_length:
													__magic_name__							:	Tuple    							=							input_ids[-self.model_max_length :]
													logger.warning(F'''Trimmed input from conversation as it was longer than {self.model_max_length} tokens.'''  )
								return input_ids









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__   (		__A:	str							,__A:	Optional[Any]							,__A:	List[Any]							,__A:	str							,__A:	List[str]=True							,__A:	List[Any]="pt"				):





					'''simple docstring'''






					__magic_name__							:	Optional[Any]    							=							{'''add_prefix_space''': True} if isinstance(__A							,__A				) and not line.startswith(''' '''				) else {}
					__magic_name__							:	List[str]    							=							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 		lowercase__   (		__A:	int							,__A:	int							,__A:	Optional[Any]=None							,):





					'''simple docstring'''






					__magic_name__							:	List[Any]    							=							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    lowerCamelCase    (		_lowerCamelCase						):






			'''simple docstring'''





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

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

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

								# Pad source and target to the right
								__magic_name__							:	int    							=							(
								    self.tokenizer.question_encoder if isinstance(self.tokenizer       ,						lowerCamelCase_  ) else self.tokenizer
								)
								__magic_name__							:	Optional[Any]    							=							self.tokenizer.generator if isinstance(self.tokenizer       ,						lowerCamelCase_  ) else self.tokenizer

								__magic_name__							:	Tuple    							=							encode_line(lowerCamelCase_       ,						lowerCamelCase_       ,						self.max_source_length       ,						'''right'''  )
								__magic_name__							:	int    							=							encode_line(lowerCamelCase_       ,						lowerCamelCase_       ,						self.max_target_length       ,						'''right'''  )

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

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


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






__lowerCamelCase   :						Dict				=			getLogger(__name__)







def 		lowercase__   (		__A:	List[List]				):





					'''simple docstring'''






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







def 		lowercase__   (		__A:	str				):





					'''simple docstring'''






					__magic_name__							:	Any    							=							get_git_info()
					save_json(__A							,os.path.join(__A							,'''git_log.json'''				)				)







def 		lowercase__   (		__A:	Optional[int]							,__A:	Union[str, Any]							,__A:	Union[str, Any]=4							,**__A:	Optional[Any]				):





					'''simple docstring'''






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







def 		lowercase__   (		__A:	List[Any]				):





					'''simple docstring'''






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







def 		lowercase__   (		):





					'''simple docstring'''






					__magic_name__							:	int    							=							git.Repo(search_parent_directories=__A				)
					__magic_name__							:	str    							=							{
					    '''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 		lowercase__   (		__A:	Callable							,__A:	Iterable				):





					'''simple docstring'''






					return list(map(__A							,__A				)				)







def 		lowercase__   (		__A:	int							,__A:	Dict				):





					'''simple docstring'''






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







def 		lowercase__   (		__A:	Any				):





					'''simple docstring'''






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

					def white_space_fix(__A:	Optional[int]				):
										return " ".join(text.split()				)

					def remove_punc(__A:	Any				):
										__magic_name__							:	Union[str, Any]    							=							set(string.punctuation				)
										return "".join(ch for ch in text if ch not in exclude				)

					def lower(__A:	Optional[int]				):
										return text.lower()

					return white_space_fix(remove_articles(remove_punc(lower(__A				)				)				)				)







def 		lowercase__   (		__A:	int							,__A:	Optional[Any]				):





					'''simple docstring'''






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







def 		lowercase__   (		__A:	List[Any]							,__A:	Dict				):





					'''simple docstring'''






					return normalize_answer(__A				) == normalize_answer(__A				)







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





					'''simple docstring'''






					assert len(__A				) == len(__A				)
					__magic_name__							:	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 		lowercase__   (		__A:	int				):





					'''simple docstring'''






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







def 		lowercase__   (		__A:	Optional[Any]							,__A:	List[str]							,__A:	Dict				):





					'''simple docstring'''






					__magic_name__							:	Tuple    							=							{p: p for p in extra_params}
					# T5 models don't have `dropout` param, they have `dropout_rate` instead
					__magic_name__							:	Any    							=							'''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
															__magic_name__							:	str    							=							p if hasattr(__A							,__A				) else equivalent_param[p]
															setattr(__A							,__A							,getattr(__A							,__A				)				)
															delattr(__A							,__A				)
					return hparams, config



