




from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


snake_case_ : Optional[Any]    		=       logging.get_logger(__name__)

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

snake_case_ : str    		=       {
    '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'
        )
    },
}

snake_case_ : Dict    		=       {
    'facebook/blenderbot_small-90M': 512,
}







class __snake_case			(			__SCREAMING_SNAKE_CASE		):
   UpperCAmelCase__  :    Optional[Any]          =  VOCAB_FILES_NAMES
   UpperCAmelCase__  :    Union[str, Any]          =  PRETRAINED_VOCAB_FILES_MAP
   UpperCAmelCase__  :    List[str]          =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   UpperCAmelCase__  :    str          =  BlenderbotSmallTokenizer







   def __init__(      self		:						Union[str, Any]					,						_snake_case		:						List[Any]=None					,						_snake_case		:						Optional[Any]=None					,						_snake_case		:						List[Any]="<|endoftext|>"					,						_snake_case		:						Optional[int]="<|endoftext|>"					,						_snake_case		:						str="<|endoftext|>"					,						_snake_case		:						Union[str, Any]=False					,						_snake_case		:						Any=True					,						**_snake_case		:						Optional[Any]					,						):

        """simple docstring"""


        super().__init__(
            ByteLevelBPETokenizer(
                vocab=_SCREAMING_SNAKE_CASE					,						merges=_SCREAMING_SNAKE_CASE					,						add_prefix_space=_SCREAMING_SNAKE_CASE					,						trim_offsets=_SCREAMING_SNAKE_CASE					,						)					,						bos_token=_SCREAMING_SNAKE_CASE					,						eos_token=_SCREAMING_SNAKE_CASE					,						unk_token=_SCREAMING_SNAKE_CASE					,						**_SCREAMING_SNAKE_CASE					,						)
        UpperCAmelCase_          =							add_prefix_space







   def lowerCamelCase						(      self		:						Dict					,						_snake_case		:						str					,						_snake_case		:						Dict=None):

        """simple docstring"""


        UpperCAmelCase_          =							[self.bos_token_id] + token_ids_a + [self.eos_token_id]
        if token_ids_a is None:
             return output

        return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







   def lowerCamelCase						(      self		:						List[str]					,						_snake_case		:						List[int]					,						_snake_case		:						Optional[List[int]] = None):

        """simple docstring"""


        UpperCAmelCase_          =							[self.sep_token_id]
        UpperCAmelCase_          =							[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]











"""simple docstring"""






import re
from pathlib import Path
from unittest import TestCase

import pytest



@pytest.mark.integration
class 			A__   (  __SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	def 							_SCREAMING_SNAKE_CASE   (     self:		Optional[int]       ,			_SCREAMING_SNAKE_CASE:		str)				->       Dict:

				"""simple docstring"""

				with open(_SCREAMING_SNAKE_CASE       ,			encoding="utf-8") as input_file:
							__lowerCAmelCase      :  List[str]												=       re.compile(r"(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)")
							__lowerCAmelCase      :  List[Any]												=       input_file.read()
							__lowerCAmelCase      :  Any												=       regexp.search(_SCREAMING_SNAKE_CASE)

				return match

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

				"""simple docstring"""

				with open(_SCREAMING_SNAKE_CASE       ,			encoding="utf-8") as input_file:
							__lowerCAmelCase      :  Any												=       re.compile(r"#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()"       ,			re.DOTALL)
							__lowerCAmelCase      :  Optional[int]												=       input_file.read()
							# use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
							__lowerCAmelCase      :  int												=       regexp.finditer(_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase      :  Union[str, Any]												=       [match for match in matches if match is not None and match.group(1) is not None]
				return matches[0] if matches else None

	def 							_SCREAMING_SNAKE_CASE   (     self:		str)				->       List[Any]:

				"""simple docstring"""

				__lowerCAmelCase      :  Optional[Any]												=       Path("./datasets")
				__lowerCAmelCase      :  Optional[int]												=       list(dataset_paths.absolute().glob("**/*.py"))

				for dataset in dataset_files:
							if self._no_encoding_on_file_open(str(_SCREAMING_SNAKE_CASE)):
										raise AssertionError(F"""open(...) must use utf-8 encoding in {dataset}""")







	def 							_SCREAMING_SNAKE_CASE   (     self:		Optional[Any])				->       Optional[int]:

				"""simple docstring"""

				__lowerCAmelCase      :  Dict												=       Path("./datasets")
				__lowerCAmelCase      :  Union[str, Any]												=       list(dataset_paths.absolute().glob("**/*.py"))

				for dataset in dataset_files:
							if self._no_print_statements(str(_SCREAMING_SNAKE_CASE)):
										raise AssertionError(F"""print statement found in {dataset}. Use datasets.logger/logging instead.""")