





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

import regex as re

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


UpperCamelCase__           =			logging.get_logger(__name__)


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

UpperCamelCase__           =			{
    "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"
        )
    },
}

UpperCamelCase__           =			{"facebook/blenderbot_small-90M": 512}





def      _UpperCamelCase  (a__ :List[Any]							):






							"""simple docstring"""





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

							UpperCamelCase__					  =      set(a__							)
							return pairs

class 							__SCREAMING_SNAKE_CASE       (  _a							):
							snake_case  :   List[str]      =							VOCAB_FILES_NAMES
							snake_case  :   Optional[int]      =							PRETRAINED_VOCAB_FILES_MAP
							snake_case  :   List[Any]      =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							snake_case  :   Any      =							["""input_ids""", """attention_mask"""]






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

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






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






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






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
														if token in self.cache:
																					return self.cache[token]
														UpperCamelCase__					  =      re.sub("""([.,!?()])"""	,			r""" \1"""	,			__lowerCAmelCase	)
														UpperCamelCase__					  =      re.sub("""(')"""	,			r""" \1 """	,			__lowerCAmelCase	)
														UpperCamelCase__					  =      re.sub(r"""\s{2,}"""	,			""" """	,			__lowerCAmelCase	)
														if "\n" in token:
																					UpperCamelCase__					  =      token.replace("""\n"""	,			""" __newln__"""	)

														UpperCamelCase__					  =      token.split(""" """	)
														UpperCamelCase__					  =      []
														for token in tokens:
																					if not len(__lowerCAmelCase	):
																												continue

																					UpperCamelCase__					  =      token.lower()
																					UpperCamelCase__					  =      tuple(__lowerCAmelCase	)
																					UpperCamelCase__					  =      tuple(list(word[:-1]	) + [word[-1] + """</w>"""]	)
																					UpperCamelCase__					  =      get_pairs(__lowerCAmelCase	)

																					if not pairs:
																												words.append(__lowerCAmelCase	)
																												continue

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

																												while i < len(__lowerCAmelCase	):
																																			try:
																																										UpperCamelCase__					  =      word.index(__lowerCAmelCase	,			__lowerCAmelCase	)
																																										new_word.extend(word[i:j]	)
																																										UpperCamelCase__					  =      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
																												UpperCamelCase__					  =      tuple(__lowerCAmelCase	)
																												UpperCamelCase__					  =      new_word
																												if len(__lowerCAmelCase	) == 1:
																																			break
																												else:
																																			UpperCamelCase__					  =      get_pairs(__lowerCAmelCase	)
																					UpperCamelCase__					  =      """@@ """.join(__lowerCAmelCase	)
																					UpperCamelCase__					  =      word[:-4]

																					UpperCamelCase__					  =      word
																					words.append(__lowerCAmelCase	)
														return " ".join(__lowerCAmelCase	)






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
														UpperCamelCase__					  =      []

														UpperCamelCase__					  =      re.findall(r"""\S+\n?"""	,			__lowerCAmelCase	)

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






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
														UpperCamelCase__					  =      token.lower()
														return self.encoder.get(__lowerCAmelCase	,			self.encoder.get(self.unk_token	)	)






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
														return self.decoder.get(__lowerCAmelCase	,			self.unk_token	)






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
														UpperCamelCase__					  =      """ """.join(__lowerCAmelCase	).replace("""@@ """	,			""""""	).strip()
														return out_string







							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase = None	):
														if not os.path.isdir(__lowerCAmelCase	):
																					logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
																					return
														UpperCamelCase__					  =      os.path.join(
														    __lowerCAmelCase	,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]	)
														UpperCamelCase__					  =      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"""	)

														UpperCamelCase__					  =      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!"""	)
																																			UpperCamelCase__					  =      token_index
																												writer.write(""" """.join(__lowerCAmelCase	) + """\n"""	)
																												index += 1

														return vocab_file, merge_file











import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


UpperCamelCase__           =			logging.get_logger(__name__)

UpperCamelCase__           =			{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

UpperCamelCase__           =			{
    "vocab_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/vocab.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/vocab.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/vocab.json",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/merges.txt",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/merges.txt",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/merges.txt",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/tokenizer.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/tokenizer.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json",
        "roberta-base-openai-detector": (
            "https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json"
        ),
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json"
        ),
    },
}

UpperCamelCase__           =			{
    "roberta-base": 512,
    "roberta-large": 512,
    "roberta-large-mnli": 512,
    "distilroberta-base": 512,
    "roberta-base-openai-detector": 512,
    "roberta-large-openai-detector": 512,
}

class 							__SCREAMING_SNAKE_CASE       (  _a							):
							snake_case  :   Optional[Any]      =							VOCAB_FILES_NAMES
							snake_case  :   Optional[Any]      =							PRETRAINED_VOCAB_FILES_MAP
							snake_case  :   Any      =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							snake_case  :   Dict      =							["""input_ids""", """attention_mask"""]
							snake_case  :   List[Any]      =							RobertaTokenizer






							def __init__(    self	,			__lowerCAmelCase=None	,			__lowerCAmelCase=None	,			__lowerCAmelCase=None	,			__lowerCAmelCase="replace"	,			__lowerCAmelCase="<s>"	,			__lowerCAmelCase="</s>"	,			__lowerCAmelCase="</s>"	,			__lowerCAmelCase="<s>"	,			__lowerCAmelCase="<unk>"	,			__lowerCAmelCase="<pad>"	,			__lowerCAmelCase="<mask>"	,			__lowerCAmelCase=False	,			__lowerCAmelCase=True	,			**__lowerCAmelCase	,			):
														super().__init__(
														    __lowerCAmelCase	,			__lowerCAmelCase	,			tokenizer_file=__lowerCAmelCase	,			errors=__lowerCAmelCase	,			bos_token=__lowerCAmelCase	,			eos_token=__lowerCAmelCase	,			sep_token=__lowerCAmelCase	,			cls_token=__lowerCAmelCase	,			unk_token=__lowerCAmelCase	,			pad_token=__lowerCAmelCase	,			mask_token=__lowerCAmelCase	,			add_prefix_space=__lowerCAmelCase	,			trim_offsets=__lowerCAmelCase	,			**__lowerCAmelCase	,			)

														UpperCamelCase__					  =      json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
														if pre_tok_state.get("""add_prefix_space"""	,			__lowerCAmelCase	) != add_prefix_space:
																					UpperCamelCase__					  =      getattr(__lowerCAmelCase	,			pre_tok_state.pop("""type"""	)	)
																					UpperCamelCase__					  =      add_prefix_space
																					UpperCamelCase__					  =      pre_tok_class(**__lowerCAmelCase	)

														UpperCamelCase__					  =      add_prefix_space

														UpperCamelCase__					  =      """post_processor"""
														UpperCamelCase__					  =      getattr(self.backend_tokenizer	,			__lowerCAmelCase	,			__lowerCAmelCase	)
														if tokenizer_component_instance:
																					UpperCamelCase__					  =      json.loads(tokenizer_component_instance.__getstate__()	)

																					# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
																					if "sep" in state:
																												UpperCamelCase__					  =      tuple(state["""sep"""]	)
																					if "cls" in state:
																												UpperCamelCase__					  =      tuple(state["""cls"""]	)

																					UpperCamelCase__					  =      False

																					if state.get("""add_prefix_space"""	,			__lowerCAmelCase	) != add_prefix_space:
																												UpperCamelCase__					  =      add_prefix_space
																												UpperCamelCase__					  =      True

																					if state.get("""trim_offsets"""	,			__lowerCAmelCase	) != trim_offsets:
																												UpperCamelCase__					  =      trim_offsets
																												UpperCamelCase__					  =      True

																					if changes_to_apply:
																												UpperCamelCase__					  =      getattr(__lowerCAmelCase	,			state.pop("""type"""	)	)
																												UpperCamelCase__					  =      component_class(**__lowerCAmelCase	)
																												setattr(self.backend_tokenizer	,			__lowerCAmelCase	,			__lowerCAmelCase	)






							@property
							def 					_lowerCamelCase		(    self	):
														if self._mask_token is None:
																					if self.verbose:
																												logger.error("""Using mask_token, but it is not set yet."""	)
																					return None
														return str(self._mask_token	)






							@mask_token.setter
							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
														UpperCamelCase__					  =      AddedToken(__lowerCAmelCase	,			lstrip=__lowerCAmelCase	,			rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,			__lowerCAmelCase	) else value
														UpperCamelCase__					  =      value






							def 					_lowerCamelCase		(    self	,			*__lowerCAmelCase	,			**__lowerCAmelCase	):
														UpperCamelCase__					  =      kwargs.get("""is_split_into_words"""	,			__lowerCAmelCase	)
														assert self.add_prefix_space or not is_split_into_words, (
														    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
														    "to use it with pretokenized inputs."
														)

														return super()._batch_encode_plus(*__lowerCAmelCase	,			**__lowerCAmelCase	)






							def 					_lowerCamelCase		(    self	,			*__lowerCAmelCase	,			**__lowerCAmelCase	):
														UpperCamelCase__					  =      kwargs.get("""is_split_into_words"""	,			__lowerCAmelCase	)

														assert self.add_prefix_space or not is_split_into_words, (
														    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
														    "to use it with pretokenized inputs."
														)

														return super()._encode_plus(*__lowerCAmelCase	,			**__lowerCAmelCase	)






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase = None	):
														UpperCamelCase__					  =      self._tokenizer.model.save(__lowerCAmelCase	,			name=__lowerCAmelCase	)
														return tuple(__lowerCAmelCase	)






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase=None	):
														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	,			__lowerCAmelCase	,			__lowerCAmelCase = None	):
														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]




