





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

SCREAMING_SNAKE_CASE_		     = logging.get_logger(__name__)


SCREAMING_SNAKE_CASE_		     = {
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

SCREAMING_SNAKE_CASE_		     = {
    """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"""
    },
}

SCREAMING_SNAKE_CASE_		     = {"""facebook/blenderbot-3B""": 1_2_8}



@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def      __lowercase     (   )				->     Tuple:


      '''simple docstring'''


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



def      __lowercase     (   _SCREAMING_SNAKE_CASE			)				->     int:


      '''simple docstring'''


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



class 	UpperCamelCase__				(   lowerCAmelCase_     ):



     '''simple docstring'''

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






     def __init__(							self		:					str		,lowerCamelCase__		:					Dict		,lowerCamelCase__		:					Union[str, Any]		,lowerCamelCase__		:					Dict="replace"		,lowerCamelCase__		:					Dict="<s>"		,lowerCamelCase__		:					Tuple="</s>"		,lowerCamelCase__		:					List[Any]="</s>"		,lowerCamelCase__		:					Dict="<s>"		,lowerCamelCase__		:					List[Any]="<unk>"		,lowerCamelCase__		:					Dict="<pad>"		,lowerCamelCase__		:					Union[str, Any]="<mask>"		,lowerCamelCase__		:					str=False		,**lowerCamelCase__		:					Tuple		,)  ->	List[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE	=		AddedToken(lowerCamelCase__		,lstrip=lowerCamelCase__		,rstrip=lowerCamelCase__ ) if isinstance(lowerCamelCase__		,lowerCamelCase__ ) else bos_token
           SCREAMING_SNAKE_CASE	=		AddedToken(lowerCamelCase__		,lstrip=lowerCamelCase__		,rstrip=lowerCamelCase__ ) if isinstance(lowerCamelCase__		,lowerCamelCase__ ) else eos_token
           SCREAMING_SNAKE_CASE	=		AddedToken(lowerCamelCase__		,lstrip=lowerCamelCase__		,rstrip=lowerCamelCase__ ) if isinstance(lowerCamelCase__		,lowerCamelCase__ ) else sep_token
           SCREAMING_SNAKE_CASE	=		AddedToken(lowerCamelCase__		,lstrip=lowerCamelCase__		,rstrip=lowerCamelCase__ ) if isinstance(lowerCamelCase__		,lowerCamelCase__ ) else cls_token
           SCREAMING_SNAKE_CASE	=		AddedToken(lowerCamelCase__		,lstrip=lowerCamelCase__		,rstrip=lowerCamelCase__ ) if isinstance(lowerCamelCase__		,lowerCamelCase__ ) else unk_token
           SCREAMING_SNAKE_CASE	=		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
           SCREAMING_SNAKE_CASE	=		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:
                 SCREAMING_SNAKE_CASE	=		json.load(lowerCamelCase__ )
           SCREAMING_SNAKE_CASE	=		{v: k for k, v in self.encoder.items()}
           SCREAMING_SNAKE_CASE	=		errors  # how to handle errors in decoding
           SCREAMING_SNAKE_CASE	=		bytes_to_unicode()
           SCREAMING_SNAKE_CASE	=		{v: k for k, v in self.byte_encoder.items()}
           with open(lowerCamelCase__		,encoding="""utf-8""" ) as merges_handle:
                 SCREAMING_SNAKE_CASE	=		merges_handle.read().split("""\n""" )[1:-1]
           SCREAMING_SNAKE_CASE	=		[tuple(merge.split() ) for merge in bpe_merges]
           SCREAMING_SNAKE_CASE	=		dict(zip(lowerCamelCase__		,range(len(lowerCamelCase__ ) ) ) )
           SCREAMING_SNAKE_CASE	=		{}
           SCREAMING_SNAKE_CASE	=		add_prefix_space

           # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
           SCREAMING_SNAKE_CASE	=		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        SCREAMING_SNAKE_CASE__						(							self		:					Union[str, Any] )  ->	List[Any]:




           '''simple docstring'''


           return len(self.encoder )






     def        SCREAMING_SNAKE_CASE__						(							self		:					Any )  ->	List[Any]:




           '''simple docstring'''


           return dict(self.encoder		,**self.added_tokens_encoder )






     def        SCREAMING_SNAKE_CASE__						(							self		:					Any		,lowerCamelCase__		:					List[Any] )  ->	Union[str, Any]:




           '''simple docstring'''


           if token in self.cache:
                 return self.cache[token]
           SCREAMING_SNAKE_CASE	=		tuple(lowerCamelCase__ )
           SCREAMING_SNAKE_CASE	=		get_pairs(lowerCamelCase__ )

           if not pairs:
                 return token

           while True:
                 SCREAMING_SNAKE_CASE	=		min(lowerCamelCase__		,key=lambda lowerCamelCase__ : self.bpe_ranks.get(lowerCamelCase__		,float("""inf""" ) ) )
                 if bigram not in self.bpe_ranks:
                       break
                 SCREAMING_SNAKE_CASE,      SCREAMING_SNAKE_CASE	=		bigram
                 SCREAMING_SNAKE_CASE	=		[]
                 SCREAMING_SNAKE_CASE	=		0
                 while i < len(lowerCamelCase__ ):
                       try:
                             SCREAMING_SNAKE_CASE	=		word.index(lowerCamelCase__		,lowerCamelCase__ )
                       except ValueError:
                             new_word.extend(word[i:] )
                             break
                       else:
                             new_word.extend(word[i:j] )
                             SCREAMING_SNAKE_CASE	=		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
                 SCREAMING_SNAKE_CASE	=		tuple(lowerCamelCase__ )
                 SCREAMING_SNAKE_CASE	=		new_word
                 if len(lowerCamelCase__ ) == 1:
                       break
                 else:
                       SCREAMING_SNAKE_CASE	=		get_pairs(lowerCamelCase__ )
           SCREAMING_SNAKE_CASE	=		""" """.join(lowerCamelCase__ )
           SCREAMING_SNAKE_CASE	=		word
           return word






     def        SCREAMING_SNAKE_CASE__						(							self		:					int		,lowerCamelCase__		:					str )  ->	Union[str, Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE	=		[]
           for token in re.findall(self.pat		,lowerCamelCase__ ):
                 SCREAMING_SNAKE_CASE	=		"""""".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        SCREAMING_SNAKE_CASE__						(							self		:					Optional[Any]		,lowerCamelCase__		:					Any )  ->	Tuple:




           '''simple docstring'''


           return self.encoder.get(lowerCamelCase__		,self.encoder.get(self.unk_token ) )






     def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[Any]		,lowerCamelCase__		:					str )  ->	List[str]:




           '''simple docstring'''


           return self.decoder.get(lowerCamelCase__ )






     def        SCREAMING_SNAKE_CASE__						(							self		:					List[Any]		,lowerCamelCase__		:					Union[str, Any] )  ->	Optional[int]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE	=		"""""".join(lowerCamelCase__ )
           SCREAMING_SNAKE_CASE	=		bytearray([self.byte_decoder[c] for c in text] ).decode("""utf-8"""		,errors=self.errors )
           return text






     def        SCREAMING_SNAKE_CASE__						(							self		:					int		,lowerCamelCase__		:					str		,lowerCamelCase__		:					Optional[str] = None )  ->	Tuple[str]:




           '''simple docstring'''


           if not os.path.isdir(lowerCamelCase__ ):
                 logger.error(F"""Vocabulary path ({save_directory}) should be a directory""" )
                 return
           SCREAMING_SNAKE_CASE	=		os.path.join(
               lowerCamelCase__		,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )
           SCREAMING_SNAKE_CASE	=		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""" )

           SCREAMING_SNAKE_CASE	=		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!""" )
                             SCREAMING_SNAKE_CASE	=		token_index
                       writer.write(""" """.join(lowerCamelCase__ ) + """\n""" )
                       index += 1

           return vocab_file, merge_file






     def        SCREAMING_SNAKE_CASE__						(							self		:					List[Any]		,lowerCamelCase__		:					List[int]		,lowerCamelCase__		:					Optional[List[int]] = None		,lowerCamelCase__		:					bool = False )  ->	List[int]:




           '''simple docstring'''


           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        SCREAMING_SNAKE_CASE__						(							self		:					Union[str, Any]		,lowerCamelCase__		:					List[int]		,lowerCamelCase__		:					Optional[List[int]] = None )  ->	List[int]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE	=		[self.sep_token_id]
           SCREAMING_SNAKE_CASE	=		[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        SCREAMING_SNAKE_CASE__						(							self		:					Dict		,lowerCamelCase__		:					str		,lowerCamelCase__		:					Dict=False		,**lowerCamelCase__		:					Optional[int] )  ->	str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE	=		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()):
                 SCREAMING_SNAKE_CASE	=		""" """ + text
           return (text, kwargs)






     def        SCREAMING_SNAKE_CASE__						(							self		:					str		,lowerCamelCase__		:					List[int]		,lowerCamelCase__		:					Optional[List[int]] = None )  ->	int:




           '''simple docstring'''


           return token_ids_a + [self.eos_token_id]






     def        SCREAMING_SNAKE_CASE__						(							self		:					Tuple		,lowerCamelCase__		:					"Conversation" )  ->	List[int]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE	=		[]
           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__ )

           SCREAMING_SNAKE_CASE	=		"""  """.join(lowerCamelCase__ )
           SCREAMING_SNAKE_CASE	=		self.encode(lowerCamelCase__ )
           if len(lowerCamelCase__ ) > self.model_max_length:
                 SCREAMING_SNAKE_CASE	=		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 pytest

from datasets import inspect_metric, list_metrics, load_metric



@pytest.fixture
def      __lowercase     (   _SCREAMING_SNAKE_CASE			)				->     List[Any]:


      '''simple docstring'''


      monkeypatch.setattr("""datasets.utils.deprecation_utils._emitted_deprecation_warnings"""				,		set()			)



@pytest.fixture
def      __lowercase     (   _SCREAMING_SNAKE_CASE			)				->     Dict:


      '''simple docstring'''


      class 	UpperCamelCase__				:



           '''simple docstring'''

           def __init__(							self		:					int		,lowerCamelCase__		:					Dict )  ->	List[Any]:




                 '''simple docstring'''


                 SCREAMING_SNAKE_CASE	=		metric_id

      class 	UpperCamelCase__				:



           '''simple docstring'''

           __snake_case					:			List[str]				=    [MetricMock(lowerCAmelCase_     ) for metric_id in ["accuracy", "mse", "precision", "codeparrot/apps_metric"]]






           def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[int] )  ->	str:




                 '''simple docstring'''


                 return self._metrics
      monkeypatch.setattr("""datasets.inspect.huggingface_hub"""				,		HfhMock()			)



@pytest.mark.parametrize(
    """func, args"""				,		[(load_metric, ("""metrics/mse""",)), (list_metrics, ()), (inspect_metric, ("""metrics/mse""", """tmp_path"""))]			)
def      __lowercase     (   _SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE			)				->     Union[str, Any]:


      '''simple docstring'''


      if "tmp_path" in args:
            SCREAMING_SNAKE_CASE	=		tuple(arg if arg != """tmp_path""" else tmp_path for arg in args			)
      with pytest.warns(_SCREAMING_SNAKE_CASE				,		match="""https://huggingface.co/docs/evaluate"""			):
            func(*_SCREAMING_SNAKE_CASE			)


