


'''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


lowercase__				     =		logging.get_logger(__name__)


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

lowercase__				     =		{
    "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"
        )
    },
}

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






def __UpperCamelCase   (			__lowerCamelCase		: Tuple				)      ->     List[str]:







     '''simple docstring'''






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

     _a						=		set(__lowerCamelCase				)
     return pairs






class 						__SCREAMING_SNAKE_CASE					(      lowerCamelCase__ ):
     UpperCAmelCase 					=				VOCAB_FILES_NAMES
     UpperCAmelCase 					=				PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase 					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase 					=				['''input_ids''', '''attention_mask''']






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

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






     @property
     def  a_					(			self		)       ->    int:
          return len(self.encoder		)






     def  a_					(			self		)       ->    Dict:
          return dict(self.encoder     ,							**self.added_tokens_encoder		)






     def  a_					(			self     ,							__UpperCamelCase		)       ->    str:
          if token in self.cache:
               return self.cache[token]
          _a						=		re.sub("([.,!?()])"     ,							R" \1"     ,							__UpperCamelCase		)
          _a						=		re.sub("(')"     ,							R" \1 "     ,							__UpperCamelCase		)
          _a						=		re.sub(R"\s{2,}"     ,							" "     ,							__UpperCamelCase		)
          if "\n" in token:
               _a						=		token.replace("\n"     ,							" __newln__"		)

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

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

               if not pairs:
                    words.append(__UpperCamelCase		)
                    continue

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

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

                         if word[i] == first and i < len(__UpperCamelCase		) - 1 and word[i + 1] == second:
                              new_word.append(first + second		)
                              i += 2
                         else:
                              new_word.append(word[i]		)
                              i += 1
                    _a						=		tuple(__UpperCamelCase		)
                    _a						=		new_word
                    if len(__UpperCamelCase		) == 1:
                         break
                    else:
                         _a						=		get_pairs(__UpperCamelCase		)
               _a						=		"@@ ".join(__UpperCamelCase		)
               _a						=		word[:-4]

               _a						=		word
               words.append(__UpperCamelCase		)
          return " ".join(__UpperCamelCase		)






     def  a_					(			self     ,							__UpperCamelCase		)       ->    List[str]:
          _a						=		[]

          _a						=		re.findall(R"\S+\n?"     ,							__UpperCamelCase		)

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






     def  a_					(			self     ,							__UpperCamelCase		)       ->    int:
          _a						=		token.lower()
          return self.encoder.get(__UpperCamelCase     ,							self.encoder.get(self.unk_token		)		)






     def  a_					(			self     ,							__UpperCamelCase		)       ->    str:
          return self.decoder.get(__UpperCamelCase     ,							self.unk_token		)






     def  a_					(			self     ,							__UpperCamelCase		)       ->    str:
          _a						=		" ".join(__UpperCamelCase		).replace("@@ "     ,							""		).strip()
          return out_string






     def  a_					(			self     ,							__UpperCamelCase     ,							__UpperCamelCase = None		)       ->    Tuple[str]:
          if not os.path.isdir(__UpperCamelCase		):
               logger.error(f"Vocabulary path ({save_directory}) should be a directory"		)
               return
          _a						=		os.path.join(
              __UpperCamelCase     ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)
          _a						=		os.path.join(
              __UpperCamelCase     ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]		)

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

          _a						=		0
          with open(__UpperCamelCase     ,							"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 __UpperCamelCase		: 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(__UpperCamelCase		) + "\n"		)
                    index += 1

          return vocab_file, merge_file





'''simple docstring'''

import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase__				     =		logging.get_logger(__name__)





class 						__SCREAMING_SNAKE_CASE					(      lowerCamelCase__ ):
     UpperCAmelCase 					=				'''encoder-decoder'''
     UpperCAmelCase 					=				True






     def __init__(			self     ,							**__UpperCamelCase		)       ->    List[Any]:
          super().__init__(**__UpperCamelCase		)
          assert (
              "encoder" in kwargs and "decoder" in kwargs
          ), "Config has to be initialized with encoder and decoder config"
          _a						=		kwargs.pop("encoder"		)
          _a						=		encoder_config.pop("model_type"		)
          _a						=		kwargs.pop("decoder"		)
          _a						=		decoder_config.pop("model_type"		)

          from ..auto.configuration_auto import AutoConfig

          _a						=		AutoConfig.for_model(__UpperCamelCase     ,							**__UpperCamelCase		)
          _a						=		AutoConfig.for_model(__UpperCamelCase     ,							**__UpperCamelCase		)
          _a						=		True






     @classmethod
     def  a_					(			cls     ,							__UpperCamelCase     ,							__UpperCamelCase     ,							**__UpperCamelCase		)       ->    PretrainedConfig:
          logger.info("Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"		)
          _a						=		True
          _a						=		True

          return cls(encoder=encoder_config.to_dict()     ,							decoder=decoder_config.to_dict()     ,							**__UpperCamelCase		)






     def  a_					(			self		)       ->    Any:
          _a						=		copy.deepcopy(self.__dict__		)
          _a						=		self.encoder.to_dict()
          _a						=		self.decoder.to_dict()
          _a						=		self.__class__.model_type
          return output

