"""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   :	Dict 					=     logging.get_logger(__name__)


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

_a   :	Optional[Any] 					=     {
    '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   :	Dict 					=     {'facebook/blenderbot_small-90M': 512}





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Union[str, Any]			) ->   Optional[Any]:
		_lowerCAmelCase		: Any						    =  set()
		_lowerCAmelCase		: List[Any]						    =  word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)			)
				_lowerCAmelCase		: int						    =  char

		_lowerCAmelCase		: List[Any]						    =  set(lowerCamelCase__			)
		return pairs






class 		__A							(				_UpperCamelCase	):
					_UpperCamelCase							:    Optional[Any]	      =	VOCAB_FILES_NAMES
					_UpperCamelCase							:    List[Any]	      =	PRETRAINED_VOCAB_FILES_MAP
					_UpperCamelCase							:    int	      =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					_UpperCamelCase							:    Any	      =	["input_ids", "attention_mask"]






					def __init__(	self       ,  a__       ,  a__       ,  a__="__start__"       ,  a__="__end__"       ,  a__="__unk__"       ,  a__="__null__"       ,  **a__       ,  ):
							super().__init__(unk_token=a__       ,  bos_token=a__       ,  eos_token=a__       ,  pad_token=a__       ,  **a__						)

							with open(a__       ,  encoding="""utf-8"""						) as vocab_handle:
									_lowerCAmelCase		: str						    =  json.load(a__						)
							_lowerCAmelCase		: Union[str, Any]						    =  {v: k for k, v in self.encoder.items()}
							with open(a__       ,  encoding="""utf-8"""						) as merges_handle:
									_lowerCAmelCase		: Optional[int]						    =  merges_handle.read().split("""\n"""						)[1:-1]
							_lowerCAmelCase		: str						    =  [tuple(merge.split()						) for merge in merges]
							_lowerCAmelCase		: List[str]						    =  dict(zip(a__       ,  range(len(a__						)						)						)						)
							_lowerCAmelCase		: Optional[Any]						    =  {}






					@property
					def 					__A						(	self						):
							return len(self.encoder						)






					def 					__A						(	self						):
							return dict(self.encoder       ,  **self.added_tokens_encoder						)






					def 					__A						(	self       ,  a__						):
							if token in self.cache:
									return self.cache[token]
							_lowerCAmelCase		: Optional[int]						    =  re.sub("""([.,!?()])"""       ,  r""" \1"""       ,  a__						)
							_lowerCAmelCase		: List[Any]						    =  re.sub("""(')"""       ,  r""" \1 """       ,  a__						)
							_lowerCAmelCase		: Optional[int]						    =  re.sub(r"""\s{2,}"""       ,  """ """       ,  a__						)
							if "\n" in token:
									_lowerCAmelCase		: Union[str, Any]						    =  token.replace("""\n"""       ,  """ __newln__"""						)

							_lowerCAmelCase		: str						    =  token.split(""" """						)
							_lowerCAmelCase		: int						    =  []
							for token in tokens:
									if not len(a__						):
											continue

									_lowerCAmelCase		: List[Any]						    =  token.lower()
									_lowerCAmelCase		: Optional[Any]						    =  tuple(a__						)
									_lowerCAmelCase		: Optional[Any]						    =  tuple(list(word[:-1]						) + [word[-1] + """</w>"""]						)
									_lowerCAmelCase		: str						    =  get_pairs(a__						)

									if not pairs:
											words.append(a__						)
											continue

									while True:
											_lowerCAmelCase		: List[Any]						    =  min(a__       ,  key=lambda a__						: self.bpe_ranks.get(a__       ,  float("""inf"""						)						)						)
											if bigram not in self.bpe_ranks:
													break
											_lowerCAmelCase		: Optional[Any]						    =  bigram
											_lowerCAmelCase		: str						    =  []
											_lowerCAmelCase		: List[Any]						    =  0

											while i < len(a__						):
													try:
															_lowerCAmelCase		: Dict						    =  word.index(a__       ,  a__						)
															new_word.extend(word[i:j]						)
															_lowerCAmelCase		: int						    =  j
													except ValueError:
															new_word.extend(word[i:]						)
															break

													if word[i] == first and i < len(a__						) - 1 and word[i + 1] == second:
															new_word.append(first + second						)
															i += 2
													else:
															new_word.append(word[i]						)
															i += 1
											_lowerCAmelCase		: Union[str, Any]						    =  tuple(a__						)
											_lowerCAmelCase		: Optional[Any]						    =  new_word
											if len(a__						) == 1:
													break
											else:
													_lowerCAmelCase		: List[Any]						    =  get_pairs(a__						)
									_lowerCAmelCase		: Optional[Any]						    =  "@@ ".join(a__						)
									_lowerCAmelCase		: Any						    =  word[:-4]

									_lowerCAmelCase		: Dict						    =  word
									words.append(a__						)
							return " ".join(a__						)






					def 					__A						(	self       ,  a__						):
							_lowerCAmelCase		: Any						    =  []

							_lowerCAmelCase		: List[Any]						    =  re.findall(r"""\S+\n?"""       ,  a__						)

							for token in words:
									split_tokens.extend(list(self.bpe(a__						).split(""" """						)						)						)
							return split_tokens






					def 					__A						(	self       ,  a__						):
							_lowerCAmelCase		: Union[str, Any]						    =  token.lower()
							return self.encoder.get(a__       ,  self.encoder.get(self.unk_token						)						)






					def 					__A						(	self       ,  a__						):
							return self.decoder.get(a__       ,  self.unk_token						)






					def 					__A						(	self       ,  a__						):
							_lowerCAmelCase		: Optional[Any]						    =  " ".join(a__						).replace("""@@ """       ,  """"""						).strip()
							return out_string






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

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

							_lowerCAmelCase		: Optional[Any]						    =  0
							with open(a__       ,  """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 a__						: 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!"""						)
													_lowerCAmelCase		: Dict						    =  token_index
											writer.write(""" """.join(a__						) + """\n"""						)
											index += 1

							return vocab_file, merge_file





"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


_a   :	Union[str, Any] 					=     {}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _a   :	Tuple 					=     ['GPTSw3Tokenizer']


if TYPE_CHECKING:
     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_gpt_swa import GPTSwaTokenizer

else:
     import sys

     _a   :	Optional[int] 					=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




