





'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple

import numpy as np

from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
    from transformers.pipelines.conversational import Conversation


a__							:							int =logging.get_logger(__name__)

a__							:							List[Any] ={'''vocab_file''': '''vocab.txt''', '''emoji_file''': '''emoji.json'''}

a__							:							int ={
    '''vocab_file''': {
        '''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/vocab.txt''',
    },
    '''emoji_file''': {
        '''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/emoji.json''',
    },
}

a__							:							Dict ={
    '''abeja/gpt-neox-japanese-2.7b''': 2_048,
}
def 				lowercase__   (   __lowercase						:  Tuple				,  __lowercase						:  Dict     ) ->      Any:



       """simple docstring"""






       with open(__lowercase				,  'r'				,  encoding='utf-8'     ) as f:
              __UpperCamelCase       =  json.loads(f.read()     )

       __UpperCamelCase       =  collections.OrderedDict()
       __UpperCamelCase       =  collections.OrderedDict()
       __UpperCamelCase       =  collections.OrderedDict()
       with open(__lowercase				,  'r'				,  encoding='utf-8'     ) as f:
              __UpperCamelCase       =  f.readlines()
       __UpperCamelCase       =  [[t.rstrip('\n'     )] if (t == ',' or ',' not in t) else t.rstrip('\n'     ).split(','     ) for t in token]
       for idx, b in enumerate(__lowercase     ):
              __UpperCamelCase       =  b
              __UpperCamelCase       =  idx
              for wd in b:
                     __UpperCamelCase       =  idx

       return vocab, raw_vocab, ids_to_tokens, emoji

class      snake_case     (    __lowerCamelCase       ):




 """simple docstring"""



 SCREAMING_SNAKE_CASE_	:					Any					=VOCAB_FILES_NAMES
 SCREAMING_SNAKE_CASE_	:					List[str]					=PRETRAINED_VOCAB_FILES_MAP
 SCREAMING_SNAKE_CASE_	:					str					=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 SCREAMING_SNAKE_CASE_	:					Dict					=["input_ids", "attention_mask"]






 def __init__(       self       :							Dict							,	__A       :							List[Any]							,	__A       :							Union[str, Any]							,	__A       :							List[str]="<|endoftext|>"							,	__A       :							int="<|endoftext|>"							,	__A       :							Optional[Any]="<|startoftext|>"							,	__A       :							Dict="<|endoftext|>"							,	__A       :							Dict=False							,	**__A       :							Any							,	):
        super().__init__(
            unk_token=__A							,	pad_token=__A							,	bos_token=__A							,	eos_token=__A							,	do_clean_text=__A							,	**__A							,	)
        if not os.path.isfile(__A	):
               raise ValueError(
                   f'''Can\'t find a vocabulary file at path \'{vocab_file}\'. To load the vocabulary from a Google pretrained'''
                   ' model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`'	)
        if not os.path.isfile(__A	):
               raise ValueError(
                   f'''Can\'t find a emoji file at path \'{emoji_file}\'. To load the emoji information from a Google'''
                   ' pretrained model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`'	)
        __UpperCamelCase       =  do_clean_text
        __UpperCamelCase       ,						__UpperCamelCase       ,						__UpperCamelCase       ,						__UpperCamelCase       =  load_vocab_and_emoji(__A							,	__A	)
        __UpperCamelCase       =  SubWordJapaneseTokenizer(
            vocab=self.vocab							,	ids_to_tokens=self.ids_to_tokens							,	emoji=self.emoji	)






 @property
 def        _lowerCamelCase					(       self       :							str	):
        # self.vocab contains support for character fluctuation unique to Japanese, and has a large number of vocab
        return len(self.raw_vocab	)






 def        _lowerCamelCase					(       self       :							Any	):
        return dict(self.raw_vocab							,	**self.added_tokens_encoder	)






 def        _lowerCamelCase					(       self       :							Optional[int]							,	__A       :							str	):
        return self.subword_tokenizer.tokenize(__A							,	clean=self.do_clean_text	)






 def        _lowerCamelCase					(       self       :							Dict							,	__A       :							int	):
        return self.vocab.get(__A							,	self.vocab.get(self.unk_token	)	)






 def        _lowerCamelCase					(       self       :							Any							,	__A       :							List[Any]	):
        return self.subword_tokenizer.convert_id_to_token(__A	)






 def        _lowerCamelCase					(       self       :							Tuple							,	__A       :							List[str]	):
        __UpperCamelCase       =  ''.join(__A	).strip()
        return out_string






 def        _lowerCamelCase					(       self       :							Union[str, Any]							,	__A       :							"Conversation"	):
        __UpperCamelCase       =  []
        for is_user, text in conversation.iter_texts():
               input_ids.extend(self.encode(__A							,	add_special_tokens=__A	) + [self.eos_token_id]	)

        if len(__A	) > self.model_max_length:
               __UpperCamelCase       =  input_ids[-self.model_max_length :]
        return input_ids






 def        _lowerCamelCase					(       self       :							List[Any]							,	__A       :							str							,	__A       :							Optional[str] = None	):
        __UpperCamelCase       =  0
        if os.path.isdir(__A	):
               __UpperCamelCase       =  os.path.join(
                   __A							,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)
               __UpperCamelCase       =  os.path.join(
                   __A							,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['emoji_file']	)
        else:
               __UpperCamelCase       =  (
                   (filename_prefix + '-' if filename_prefix else '') + save_directory + VOCAB_FILES_NAMES['vocab_file']
               )
               __UpperCamelCase       =  (
                   (filename_prefix + '-' if filename_prefix else '') + save_directory + VOCAB_FILES_NAMES['emoji_file']
               )
        with open(__A							,	'w'							,	encoding='utf-8'	) as writer:
               for token_index, token in self.ids_to_tokens.items():
                      if index != token_index:
                             logger.warning(
                                 f'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
                                 ' Please check that the vocabulary is not corrupted!'	)
                             __UpperCamelCase       =  token_index
                      writer.write(','.join(__A	) + '\n'	)
                      index += 1
        with open(__A							,	'w'							,	encoding='utf-8'	) as writer:
               json.dump(self.emoji							,	__A	)
        return vocab_file, emoji_file






class      snake_case     (    __lowerCamelCase       ):




 """simple docstring"""



 def __init__(       self       :							Optional[Any]							,	__A       :							Optional[int]							,	__A       :							List[str]							,	__A       :							Dict	):
        __UpperCamelCase       =  vocab  # same as swe
        __UpperCamelCase       =  ids_to_tokens  # same as bpe
        __UpperCamelCase       =  emoji
        __UpperCamelCase       =  np.max([len(__A	) for w in self.vocab.keys()]	)
        __UpperCamelCase       =  re.compile(R'(https?|ftp)(:\/\/[-_\.!~*\'()a-zA-Z0-9;\/?:\@&=\+$,%#]+)'	)
        __UpperCamelCase       =  re.compile(R'[A-Za-z0-9\._+]*@[\-_0-9A-Za-z]+(\.[A-Za-z]+)*'	)
        __UpperCamelCase       =  re.compile(R'[\(]{0,1}[0-9]{2,4}[\)\-\(]{0,1}[0-9]{2,4}[\)\-]{0,1}[0-9]{3,4}'	)
        __UpperCamelCase       =  re.compile(
            R'([12]\d{3}[/\-年])*(0?[1-9]|1[0-2])[/\-月]((0?[1-9]|[12][0-9]|3[01])日?)*(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*'	)
        __UpperCamelCase       =  re.compile(
            R'(明治|大正|昭和|平成|令和|㍾|㍽|㍼|㍻|\u32ff)\d{1,2}年(0?[1-9]|1[0-2])月(0?[1-9]|[12][0-9]|3[01])日(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*'	)
        __UpperCamelCase       =  re.compile(
            R'((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*億)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*万)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*千)*(0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*(千円|万円|千万円|円|千ドル|万ドル|千万ドル|ドル|千ユーロ|万ユーロ|千万ユーロ|ユーロ)+(\(税込\)|\(税抜\)|\+tax)*'	)
        __UpperCamelCase       =  '─━│┃┄┅┆┇┈┉┊┋┌┍┎┏┐┑┒┓└┕┖┗┘┙┚┛├┝┞┟┠┡┢┣┤┥┦┧┨┩┪┫┬┭┮┯┰┱┲┳┴┵┶┷┸┹┺┻┼┽┾┿╀╁╂╃╄╅╆╇╈╉╊╋╌╍╎╏═║╒╓╔╕╖╗╘╙╚╛╜╝╞╟╠╡╢╣╤╥╦╧╨╩╪╫╬╭╮╯╰╱╲╳╴╵╶╷╸╹╺╻╼╽╾╿'
        __UpperCamelCase       =  '▀▁▂▃▄▅▆▇█▉▊▋▌▍▎▏▐░▒▓▔▕▖▗▘▙▚▛▜▝▞▟'
        __UpperCamelCase       =  str.maketrans({k: '<BLOCK>' for k in keisen + blocks}	)






 def __len__(       self       :							List[Any]	):
        return len(self.ids_to_tokens	)






 def        _lowerCamelCase					(       self       :							List[str]							,	__A       :							List[str]	):
        __UpperCamelCase       =  self.content_repattera.sub('<URL>'							,	__A	)
        __UpperCamelCase       =  self.content_repattera.sub('<EMAIL>'							,	__A	)
        __UpperCamelCase       =  self.content_repattera.sub('<TEL>'							,	__A	)
        __UpperCamelCase       =  self.content_repattera.sub('<DATE>'							,	__A	)
        __UpperCamelCase       =  self.content_repattera.sub('<DATE>'							,	__A	)
        __UpperCamelCase       =  self.content_repattera.sub('<PRICE>'							,	__A	)
        __UpperCamelCase       =  content.translate(self.content_transa	)
        while "<BLOCK><BLOCK>" in content:
               __UpperCamelCase       =  content.replace('<BLOCK><BLOCK>'							,	'<BLOCK>'	)
        return content






 def        _lowerCamelCase					(       self       :							List[Any]							,	__A       :							Any							,	__A       :							Union[str, Any]=False	):
        __UpperCamelCase       =  text.replace(' '							,	'<SP>'	)
        __UpperCamelCase       =  text.replace('　'							,	'<SP>'	)
        __UpperCamelCase       =  text.replace('\r\n'							,	'<BR>'	)
        __UpperCamelCase       =  text.replace('\n'							,	'<BR>'	)
        __UpperCamelCase       =  text.replace('\r'							,	'<BR>'	)
        __UpperCamelCase       =  text.replace('\t'							,	'<TAB>'	)
        __UpperCamelCase       =  text.replace('—'							,	'ー'	)
        __UpperCamelCase       =  text.replace('−'							,	'ー'	)
        for k, v in self.emoji["emoji"].items():
               if k in text:
                      __UpperCamelCase       =  text.replace(__A							,	__A	)
        if clean:
               __UpperCamelCase       =  self.clean_text(__A	)

        def check_simbol(__A       :							str	):
               __UpperCamelCase       =  x.encode()
               if len(__A	) == 1 and len(__A	) == 2:
                      __UpperCamelCase       =  (int(e[0]	) << 8) + int(e[1]	)
                      if (
                          (c >= 0xc2a1 and c <= 0xc2bf)
                          or (c >= 0xc780 and c <= 0xc783)
                          or (c >= 0xcab9 and c <= 0xcbbf)
                          or (c >= 0xcc80 and c <= 0xcda2)
                      ):
                             return True
               return False

        def checkuae(__A       :							Tuple	):
               __UpperCamelCase       =  x.encode()
               if len(__A	) == 1 and len(__A	) == 3:
                      __UpperCamelCase       =  (int(e[0]	) << 1_6) + (int(e[1]	) << 8) + int(e[2]	)
                      if c >= 0xe2_8080 and c <= 0xe2_b07f:
                             return True
               return False

        __UpperCamelCase       =  0
        __UpperCamelCase       =  []
        while pos < len(__A	):
               __UpperCamelCase       =  min(len(__A	)							,	pos + self.maxlen + 1	) if text[pos] == '<' else pos + 3
               __UpperCamelCase       =  []  # (token_id, token, pos)
               for e in range(__A							,	__A							,	-1	):
                      __UpperCamelCase       =  text[pos:e]
                      if wd in self.vocab:
                             if wd[0] == "<" and len(__A	) > 2:
                                    __UpperCamelCase       =  [(self.vocab[wd], wd, e)]
                                    break
                             else:
                                    candidates.append((self.vocab[wd], wd, e)	)
               if len(__A	) > 0:
                      # the smallest token_id is adopted
                      __UpperCamelCase       ,						__UpperCamelCase       ,						__UpperCamelCase       =  sorted(__A							,	key=lambda __A	: x[0]	)[0]
                      result.append(__A	)
                      __UpperCamelCase       =  e
               else:
                      __UpperCamelCase       =  pos + 1
                      __UpperCamelCase       =  text[pos:end]
                      if check_simbol(__A	):
                             result.append('<KIGOU>'	)
                      elif checkuae(__A	):
                             result.append('<U2000U2BFF>'	)
                      else:
                             for i in wd.encode('utf-8'	):
                                    result.append('<|byte%d|>' % i	)
                      __UpperCamelCase       =  end
        return result






 def        _lowerCamelCase					(       self       :							Union[str, Any]							,	__A       :							Any							,	__A       :							List[Any]="\n"	):
        __UpperCamelCase       =  []
        __UpperCamelCase       =  []
        __UpperCamelCase       =  self.ids_to_tokens[index][0]
        if word[:6] == "<|byte" and word[-2:] == "|>":
               byte_tokens.append(int(word[6:-2]	)	)
        else:
               if len(__A	) > 0:
                      words.append(bytearray(__A	).decode('utf-8'							,	errors='replace'	)	)
                      __UpperCamelCase       =  []
               if word[:7] == "<|emoji" and word[-2:] == "|>":
                      words.append(self.emoji['emoji_inv'][word]	)
               elif word == "<SP>":
                      words.append(' '	)
               elif word == "<BR>":
                      words.append(__A	)
               elif word == "<TAB>":
                      words.append('\t'	)
               elif word == "<BLOCK>":
                      words.append('▀'	)
               elif word == "<KIGOU>":
                      words.append('ǀ'	)
               elif word == "<U2000U2BFF>":
                      words.append('‖'	)
               else:
                      words.append(__A	)
        if len(__A	) > 0:
               words.append(bytearray(__A	).decode('utf-8'							,	errors='replace'	)	)
        __UpperCamelCase       =  ''.join(__A	)
        return text





"""simple docstring"""






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      snake_case__   (		__lowerCamelCase				:    Union[str, Any]							,		__lowerCamelCase				:    Tuple							,		__lowerCamelCase				:    Any							,		__lowerCamelCase				:    Tuple							,		__lowerCamelCase				:    Tuple=True							,		__lowerCamelCase				:    Dict="pt"	):
			"""simple docstring"""
			lowerCamelCase__		:		str			={'''add_prefix_space''': True} if isinstance(__lowerCamelCase							,		__lowerCamelCase	) and not line.startswith(''' '''	) else {}
			lowerCamelCase__		:		int			=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      snake_case__   (		__lowerCamelCase				:    str							,		__lowerCamelCase				:    List[Any]							,		__lowerCamelCase				:    Optional[int]=None							,		):
			"""simple docstring"""
			lowerCamelCase__		:		Any			=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        __SCREAMING_SNAKE_CASE	(      lowerCAmelCase_   ):


					'''simple docstring'''





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



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



					def __getitem__(       self							:  List[str],  lowerCamelCase							:  Optional[int]     )->					Dict[str, torch.Tensor]:
								lowerCamelCase__		:		List[Any]			=index + 1  # linecache starts at 1
								lowerCamelCase__		:		Optional[int]			=self.prefix + linecache.getline(str(self.src_file     ),  lowerCamelCase     ).rstrip('''\n'''     )
								lowerCamelCase__		:		Optional[Any]			=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
								lowerCamelCase__		:		Optional[int]			=(
								    self.tokenizer.question_encoder if isinstance(self.tokenizer,  lowerCamelCase     ) else self.tokenizer
								)
								lowerCamelCase__		:		Tuple			=self.tokenizer.generator if isinstance(self.tokenizer,  lowerCamelCase     ) else self.tokenizer

								lowerCamelCase__		:		Optional[int]			=encode_line(lowerCamelCase,  lowerCamelCase,  self.max_source_length,  '''right'''     )
								lowerCamelCase__		:		str			=encode_line(lowerCamelCase,  lowerCamelCase,  self.max_target_length,  '''right'''     )

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



					@staticmethod
					def 		snake_case       (       lowerCamelCase							:  Union[str, Any]     )->					Optional[int]:
								return [len(lowerCamelCase     ) for x in Path(lowerCamelCase     ).open().readlines()]




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





_lowercase : Any      						=						getLogger(__name__)






def      snake_case__   (		__lowerCamelCase				:    List[List]	):
			"""simple docstring"""
			return list(itertools.chain.from_iterable(__lowerCamelCase	)	)






def      snake_case__   (		__lowerCamelCase				:    str	):
			"""simple docstring"""
			lowerCamelCase__		:		Dict			=get_git_info()
			save_json(__lowerCamelCase							,		os.path.join(__lowerCamelCase							,		'''git_log.json'''	)	)






def      snake_case__   (		__lowerCamelCase				:    Union[str, Any]							,		__lowerCamelCase				:    Optional[int]							,		__lowerCamelCase				:    Dict=4							,		**__lowerCamelCase				:    int	):
			"""simple docstring"""
			with open(__lowerCamelCase							,		'''w'''	) as f:
						json.dump(__lowerCamelCase							,		__lowerCamelCase							,		indent=__lowerCamelCase							,		**__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    List[Any]	):
			"""simple docstring"""
			with open(__lowerCamelCase	) as f:
						return json.load(__lowerCamelCase	)






def      snake_case__   (		):
			"""simple docstring"""
			lowerCamelCase__		:		List[Any]			=git.Repo(search_parent_directories=__lowerCamelCase	)
			lowerCamelCase__		:		Union[str, Any]			={
			    '''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      snake_case__   (		__lowerCamelCase				:    Callable							,		__lowerCamelCase				:    Iterable	):
			"""simple docstring"""
			return list(map(__lowerCamelCase							,		__lowerCamelCase	)	)






def      snake_case__   (		__lowerCamelCase				:    Any							,		__lowerCamelCase				:    List[Any]	):
			"""simple docstring"""
			with open(__lowerCamelCase							,		'''wb'''	) as f:
						return pickle.dump(__lowerCamelCase							,		__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    str	):
			"""simple docstring"""

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

			def white_space_fix(__lowerCamelCase				:    Any	):
						return " ".join(text.split()	)

			def remove_punc(__lowerCamelCase				:    Optional[Any]	):
						lowerCamelCase__		:		Tuple			=set(string.punctuation	)
						return "".join(ch for ch in text if ch not in exclude	)

			def lower(__lowerCamelCase				:    Any	):
						return text.lower()

			return white_space_fix(remove_articles(remove_punc(lower(__lowerCamelCase	)	)	)	)






def      snake_case__   (		__lowerCamelCase				:    List[str]							,		__lowerCamelCase				:    List[str]	):
			"""simple docstring"""
			lowerCamelCase__		:		List[str]			=normalize_answer(__lowerCamelCase	).split()
			lowerCamelCase__		:		List[str]			=normalize_answer(__lowerCamelCase	).split()
			lowerCamelCase__		:		Optional[int]			=Counter(__lowerCamelCase	) & Counter(__lowerCamelCase	)
			lowerCamelCase__		:		Union[str, Any]			=sum(common.values()	)
			if num_same == 0:
						return 0
			lowerCamelCase__		:		Dict			=1.0 * num_same / len(__lowerCamelCase	)
			lowerCamelCase__		:		List[str]			=1.0 * num_same / len(__lowerCamelCase	)
			lowerCamelCase__		:		Union[str, Any]			=(2 * precision * recall) / (precision + recall)
			return fa






def      snake_case__   (		__lowerCamelCase				:    Dict							,		__lowerCamelCase				:    int	):
			"""simple docstring"""
			return normalize_answer(__lowerCamelCase	) == normalize_answer(__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    List[str]							,		__lowerCamelCase				:    List[str]	):
			"""simple docstring"""
			assert len(__lowerCamelCase	) == len(__lowerCamelCase	)
			lowerCamelCase__		:		Any			=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      snake_case__   (		__lowerCamelCase				:    List[str]	):
			"""simple docstring"""
			return model_prefix.startswith('''rag'''	)






def      snake_case__   (		__lowerCamelCase				:    Any							,		__lowerCamelCase				:    List[str]							,		__lowerCamelCase				:    str	):
			"""simple docstring"""
			lowerCamelCase__		:		Any			={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(__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
									lowerCamelCase__		:		List[Any]			=p if hasattr(__lowerCamelCase							,		__lowerCamelCase	) else equivalent_param[p]
									setattr(__lowerCamelCase							,		__lowerCamelCase							,		getattr(__lowerCamelCase							,		__lowerCamelCase	)	)
									delattr(__lowerCamelCase							,		__lowerCamelCase	)
			return hparams, config




