




"""simple docstring"""

import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a							      =     logging.get_logger(__name__)


a							      =     {
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

a							      =     {
    '''vocab_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'''
    },
    '''merges_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'''
    },
    '''tokenizer_config_file''': {
        '''facebook/blenderbot_small-90M''': (
            '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'''
        )
    },
}

a							      =     {'''facebook/blenderbot_small-90M''': 512}






def 		_snake_case	(   _snake_case				:   List[str]				)       ->   Union[str, Any]:






      '''simple docstring'''


      _A     =  set()
      _A     =  word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)				)
            _A     =  char

      _A     =  set(_snake_case				)
      return pairs







class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	List[str]     =      VOCAB_FILES_NAMES
 UpperCAmelCase       :	Optional[int]     =      PRETRAINED_VOCAB_FILES_MAP
 UpperCAmelCase       :	int     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCAmelCase       :	List[Any]     =      ['''input_ids''', '''attention_mask''']

 def __init__(					self			:			int       ,				_UpperCAmelCase			:			Tuple       ,				_UpperCAmelCase			:			str       ,				_UpperCAmelCase			:			Tuple="__start__"       ,				_UpperCAmelCase			:			int="__end__"       ,				_UpperCAmelCase			:			Optional[Any]="__unk__"       ,				_UpperCAmelCase			:			List[str]="__null__"       ,				**_UpperCAmelCase			:			str       ,				):
       super().__init__(unk_token=_UpperCAmelCase       ,				bos_token=_UpperCAmelCase       ,				eos_token=_UpperCAmelCase       ,				pad_token=_UpperCAmelCase       ,				**_UpperCAmelCase						)

       with open(_UpperCAmelCase       ,				encoding='utf-8'						) as vocab_handle:
             _A     =  json.load(_UpperCAmelCase						)
       _A     =  {v: k for k, v in self.encoder.items()}
       with open(_UpperCAmelCase       ,				encoding='utf-8'						) as merges_handle:
             _A     =  merges_handle.read().split('\n'						)[1:-1]
       _A     =  [tuple(merge.split()						) for merge in merges]
       _A     =  dict(zip(_UpperCAmelCase       ,				range(len(_UpperCAmelCase						)						)						)						)
       _A     =  {}

 @property
 def      lowerCAmelCase_				(					self			:			Optional[Any]						):
       return len(self.encoder						)

 def      lowerCAmelCase_				(					self			:			Union[str, Any]						):
       return dict(self.encoder       ,				**self.added_tokens_encoder						)

 def      lowerCAmelCase_				(					self			:			Optional[int]       ,				_UpperCAmelCase			:			str						):
       if token in self.cache:
             return self.cache[token]
       _A     =  re.sub('([.,!?()])'       ,				r' \1'       ,				_UpperCAmelCase						)
       _A     =  re.sub('(\')'       ,				r' \1 '       ,				_UpperCAmelCase						)
       _A     =  re.sub(r'\s{2,}'       ,				' '       ,				_UpperCAmelCase						)
       if "\n" in token:
             _A     =  token.replace('\n'       ,				' __newln__'						)

       _A     =  token.split(' '						)
       _A     =  []
       for token in tokens:
             if not len(_UpperCAmelCase						):
                   continue

             _A     =  token.lower()
             _A     =  tuple(_UpperCAmelCase						)
             _A     =  tuple(list(word[:-1]						) + [word[-1] + '</w>']						)
             _A     =  get_pairs(_UpperCAmelCase						)

             if not pairs:
                   words.append(_UpperCAmelCase						)
                   continue

             while True:
                   _A     =  min(_UpperCAmelCase       ,				key=lambda _UpperCAmelCase						: self.bpe_ranks.get(_UpperCAmelCase       ,				float('inf'						)						)						)
                   if bigram not in self.bpe_ranks:
                         break
                   _A  ,       _A     =  bigram
                   _A     =  []
                   _A     =  0

                   while i < len(_UpperCAmelCase						):
                         try:
                               _A     =  word.index(_UpperCAmelCase       ,				_UpperCAmelCase						)
                               new_word.extend(word[i:j]						)
                               _A     =  j
                         except ValueError:
                               new_word.extend(word[i:]						)
                               break

                         if word[i] == first and i < len(_UpperCAmelCase						) - 1 and word[i + 1] == second:
                               new_word.append(first + second						)
                               i += 2
                         else:
                               new_word.append(word[i]						)
                               i += 1
                   _A     =  tuple(_UpperCAmelCase						)
                   _A     =  new_word
                   if len(_UpperCAmelCase						) == 1:
                         break
                   else:
                         _A     =  get_pairs(_UpperCAmelCase						)
             _A     =  '@@ '.join(_UpperCAmelCase						)
             _A     =  word[:-4]

             _A     =  word
             words.append(_UpperCAmelCase						)
       return " ".join(_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Optional[int]       ,				_UpperCAmelCase			:			str						):
       _A     =  []

       _A     =  re.findall(r'\S+\n?'       ,				_UpperCAmelCase						)

       for token in words:
             split_tokens.extend(list(self.bpe(_UpperCAmelCase						).split(' '						)						)						)
       return split_tokens

 def      lowerCAmelCase_				(					self			:			List[str]       ,				_UpperCAmelCase			:			str						):
       _A     =  token.lower()
       return self.encoder.get(_UpperCAmelCase       ,				self.encoder.get(self.unk_token						)						)

 def      lowerCAmelCase_				(					self			:			Tuple       ,				_UpperCAmelCase			:			int						):
       return self.decoder.get(_UpperCAmelCase       ,				self.unk_token						)

 def      lowerCAmelCase_				(					self			:			Dict       ,				_UpperCAmelCase			:			List[str]						):
       _A     =  ' '.join(_UpperCAmelCase						).replace('@@ '       ,				''						).strip()
       return out_string



 def      lowerCAmelCase_				(					self			:			Optional[int]       ,				_UpperCAmelCase			:			str       ,				_UpperCAmelCase			:			Optional[str] = None						):
       if not os.path.isdir(_UpperCAmelCase						):
             logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''						)
             return
       _A     =  os.path.join(
           _UpperCAmelCase       ,				(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']						)
       _A     =  os.path.join(
           _UpperCAmelCase       ,				(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']						)

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

       _A     =  0
       with open(_UpperCAmelCase       ,				'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 _UpperCAmelCase						: 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!'						)
                         _A     =  token_index
                   writer.write(' '.join(_UpperCAmelCase						) + '\n'						)
                   index += 1

       return vocab_file, merge_file







"""simple docstring"""

import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


a							      =     logging.getLogger(__name__)





@dataclass
class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	Optional[float]     =      field(
     default=0.0     ,      metadata={'''help''': '''The label smoothing epsilon to apply (if not zero).'''}				)
 UpperCAmelCase       :	bool     =      field(default=__lowerCAmelCase     ,      metadata={'''help''': '''Whether to SortishSamler or not.'''}				)
 UpperCAmelCase       :	bool     =      field(
     default=__lowerCAmelCase     ,      metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}				)
 UpperCAmelCase       :	bool     =      field(default=__lowerCAmelCase     ,      metadata={'''help''': '''whether to use adafactor'''}				)
 UpperCAmelCase       :	Optional[float]     =      field(
     default=__lowerCAmelCase     ,      metadata={'''help''': '''Encoder layer dropout probability. Goes into model.config.'''}				)
 UpperCAmelCase       :	Optional[float]     =      field(
     default=__lowerCAmelCase     ,      metadata={'''help''': '''Decoder layer dropout probability. Goes into model.config.'''}				)
 UpperCAmelCase       :	Optional[float]     =      field(default=__lowerCAmelCase     ,      metadata={'''help''': '''Dropout probability. Goes into model.config.'''}				)
 UpperCAmelCase       :	Optional[float]     =      field(
     default=__lowerCAmelCase     ,      metadata={'''help''': '''Attention dropout probability. Goes into model.config.'''}				)
 UpperCAmelCase       :	Optional[str]     =      field(
     default='''linear'''     ,      metadata={'''help''': f'''Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()				)}'''}     ,      )

