



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

import regex as re

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


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_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'''
        )
    },
}

SCREAMING_SNAKE_CASE__       =      {'''facebook/blenderbot_small-90M''': 5_1_2}


def A						(       __UpperCamelCase					)						->      str:
			A__       =    set()
			A__       =    word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)					)
						A__       =    char

			A__       =    set(snake_case__					)
			return pairs






class      __lowerCAmelCase     (		__lowerCAmelCase      ):
					"""simple docstring"""






					A__				:		List[Any]			       =    VOCAB_FILES_NAMES
					A__				:		Tuple			       =    PRETRAINED_VOCAB_FILES_MAP
					A__				:		List[str]			       =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A__				:		int			       =    ['''input_ids''', '''attention_mask''']



					def __init__(     self					:       Optional[Any]				,					_snake_case					:       List[Any]				,					_snake_case					:       Union[str, Any]				,					_snake_case					:       int="__start__"				,					_snake_case					:       Dict="__end__"				,					_snake_case					:       Dict="__unk__"				,					_snake_case					:       Tuple="__null__"				,					**_snake_case					:       Optional[Any]				,					):






								"""simple docstring"""


								super().__init__(unk_token=lowerCAmelCase_				,					bos_token=lowerCAmelCase_				,					eos_token=lowerCAmelCase_				,					pad_token=lowerCAmelCase_				,					**lowerCAmelCase_					)

								with open(lowerCAmelCase_				,					encoding='utf-8'					) as vocab_handle:
											A__       =    json.load(lowerCAmelCase_					)
								A__       =    {v: k for k, v in self.encoder.items()}
								with open(lowerCAmelCase_				,					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(lowerCAmelCase_				,					range(len(lowerCAmelCase_					)					)					)					)
								A__       =    {}



					@property
					def     _a							(     self					:       Tuple					):






								"""simple docstring"""


								return len(self.encoder					)



					def     _a							(     self					:       Tuple					):






								"""simple docstring"""


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



					def     _a							(     self					:       str				,					_snake_case					:       List[str]					):






								"""simple docstring"""


								if token in self.cache:
											return self.cache[token]
								A__       =    re.sub('([.,!?()])'				,					R' \1'				,					lowerCAmelCase_					)
								A__       =    re.sub('(\')'				,					R' \1 '				,					lowerCAmelCase_					)
								A__       =    re.sub(R'\s{2,}'				,					' '				,					lowerCAmelCase_					)
								if "\n" in token:
											A__       =    token.replace('\n'				,					' __newln__'					)

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

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

											if not pairs:
														words.append(lowerCAmelCase_					)
														continue

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

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

																	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
														A__       =    tuple(lowerCAmelCase_					)
														A__       =    new_word
														if len(lowerCAmelCase_					) == 1:
																	break
														else:
																	A__       =    get_pairs(lowerCAmelCase_					)
											A__       =    '@@ '.join(lowerCAmelCase_					)
											A__       =    word[:-4]

											A__       =    word
											words.append(lowerCAmelCase_					)
								return " ".join(lowerCAmelCase_					)



					def     _a							(     self					:       List[str]				,					_snake_case					:       Dict					):






								"""simple docstring"""


								A__       =    []

								A__       =    re.findall(R'\S+\n?'				,					lowerCAmelCase_					)

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



					def     _a							(     self					:       Dict				,					_snake_case					:       Optional[Any]					):






								"""simple docstring"""


								A__       =    token.lower()
								return self.encoder.get(lowerCAmelCase_				,					self.encoder.get(self.unk_token					)					)



					def     _a							(     self					:       Dict				,					_snake_case					:       List[Any]					):






								"""simple docstring"""


								return self.decoder.get(lowerCAmelCase_				,					self.unk_token					)



					def     _a							(     self					:       Dict				,					_snake_case					:       Tuple					):






								"""simple docstring"""


								A__       =    ' '.join(lowerCAmelCase_					).replace('@@ '				,					''					).strip()
								return out_string



					def     _a							(     self					:       int				,					_snake_case					:       Dict				,					_snake_case					:       Dict = None					):






								"""simple docstring"""


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

								A__       =    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 _snake_case					: 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(lowerCAmelCase_					) + '\n'					)
														index += 1

								return vocab_file, merge_file









import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
							from .tokenization_rembert import RemBertTokenizer
else:
							SCREAMING_SNAKE_CASE__       =      None

SCREAMING_SNAKE_CASE__       =      logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__       =      {'''vocab_file''': '''sentencepiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

SCREAMING_SNAKE_CASE__       =      {
    '''vocab_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/sentencepiece.model''',
    },
    '''tokenizer_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/tokenizer.json''',
    },
}

SCREAMING_SNAKE_CASE__       =      {
    '''google/rembert''': 2_5_6,
}

SCREAMING_SNAKE_CASE__       =      '''▁'''


class      __lowerCAmelCase     (		UpperCAmelCase_      ):
					"""simple docstring"""






					A__				:		Any			       =    VOCAB_FILES_NAMES
					A__				:		str			       =    PRETRAINED_VOCAB_FILES_MAP
					A__				:		str			       =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A__				:		int			       =    RemBertTokenizer



					def __init__(     self					:       Union[str, Any]				,					_snake_case					:       Any=None				,					_snake_case					:       Optional[Any]=None				,					_snake_case					:       Any=True				,					_snake_case					:       Optional[int]=True				,					_snake_case					:       Dict=False				,					_snake_case					:       Dict="[CLS]"				,					_snake_case					:       List[Any]="[SEP]"				,					_snake_case					:       Union[str, Any]="<unk>"				,					_snake_case					:       List[str]="[SEP]"				,					_snake_case					:       List[str]="<pad>"				,					_snake_case					:       str="[CLS]"				,					_snake_case					:       Any="[MASK]"				,					**_snake_case					:       Any				,					):






								"""simple docstring"""


								A__       =    AddedToken(_snake_case				,					lstrip=_snake_case				,					rstrip=_snake_case					) if isinstance(_snake_case				,					_snake_case					) else mask_token

								super().__init__(
								    _snake_case				,					tokenizer_file=_snake_case				,					do_lower_case=_snake_case				,					remove_space=_snake_case				,					keep_accents=_snake_case				,					bos_token=_snake_case				,					eos_token=_snake_case				,					unk_token=_snake_case				,					sep_token=_snake_case				,					pad_token=_snake_case				,					cls_token=_snake_case				,					mask_token=_snake_case				,					**_snake_case				,					)

								A__       =    do_lower_case
								A__       =    remove_space
								A__       =    keep_accents
								A__       =    vocab_file
								A__       =    False if not self.vocab_file else True



					def     _a							(     self					:       Any				,					_snake_case					:       List[int]				,					_snake_case					:       Optional[List[int]] = None					):






								"""simple docstring"""


								A__       =    [self.sep_token_id]
								A__       =    [self.cls_token_id]
								if token_ids_a is None:
											return cls + token_ids_a + sep
								return cls + token_ids_a + sep + token_ids_a + sep



					def     _a							(     self					:       Tuple				,					_snake_case					:       List[int]				,					_snake_case					:       Optional[List[int]] = None				,					_snake_case					:       bool = False					):






								"""simple docstring"""


								if already_has_special_tokens:
											if token_ids_a is not None:
														raise ValueError(
														    'You should not supply a second sequence if the provided sequence of '
														    'ids is already formatted with special tokens for the model.'					)
											return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

								if token_ids_a is not None:
											return [1] + ([0] * len(_snake_case					)) + [1] + ([0] * len(_snake_case					)) + [1]
								return [1] + ([0] * len(_snake_case					)) + [1]



					def     _a							(     self					:       Dict				,					_snake_case					:       List[int]				,					_snake_case					:       Optional[List[int]] = None					):






								"""simple docstring"""


								A__       =    [self.sep_token_id]
								A__       =    [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					) * [0] + len(token_ids_a + sep					) * [1]



					def     _a							(     self					:       Any				,					_snake_case					:       str				,					_snake_case					:       Optional[str] = None					):






								"""simple docstring"""


								if not os.path.isdir(_snake_case					):
											logger.error('Vocabulary path ({}) should be a directory'.format(_snake_case					)					)
											return
								A__       =    os.path.join(
								    _snake_case				,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']					)

								if os.path.abspath(self.vocab_file					) != os.path.abspath(_snake_case					):
											copyfile(self.vocab_file				,					_snake_case					)

								return (out_vocab_file,)




