



import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
		from transformers.pipelines.conversational import Conversation

__lowerCamelCase     :							str  							=				logging.get_logger(__name__)


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

__lowerCamelCase     :							Optional[Any]  							=				{
    "vocab_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json"},
    "merges_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt"},
    "tokenizer_config_file": {
        "facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json"
    },
}

__lowerCamelCase     :							Tuple  							=				{"facebook/blenderbot-3B": 128}

@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def    lowerCamelCase_() ->       Dict:

						'''simple docstring'''





						UpperCAmelCase         =     (
						    list(range(ord("!"    )    ,   ord("~"    ) + 1    )    ) + list(range(ord("¡"    )    ,   ord("¬"    ) + 1    )    ) + list(range(ord("®"    )    ,   ord("ÿ"    ) + 1    )    )
						)
						UpperCAmelCase         =     bs[:]
						UpperCAmelCase         =     0
						for b in range(2**8    ):
												if b not in bs:
																		bs.append(lowerCamelCase_    )
																		cs.append(2**8 + n    )
																		n += 1
						UpperCAmelCase         =     [chr(lowerCamelCase_    ) for n in cs]
						return dict(zip(lowerCamelCase_    ,   lowerCamelCase_    )    )

def    lowerCamelCase_(lowerCamelCase_    ) ->       Dict:

						'''simple docstring'''





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





class  __magic_name__   (							A__						):
		lowercase      :       int          =VOCAB_FILES_NAMES
		lowercase      :       int          =PRETRAINED_VOCAB_FILES_MAP
		lowercase      :       Any          =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowercase      :       List[str]          =['''input_ids''', '''attention_mask''']






		def __init__(						self      :     Optional[Any]				,		UpperCamelCase__      :     Tuple				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     Tuple="replace"				,		UpperCamelCase__      :     Union[str, Any]="<s>"				,		UpperCamelCase__      :     List[Any]="</s>"				,		UpperCamelCase__      :     int="</s>"				,		UpperCamelCase__      :     Dict="<s>"				,		UpperCamelCase__      :     Dict="<unk>"				,		UpperCamelCase__      :     Optional[Any]="<pad>"				,		UpperCamelCase__      :     int="<mask>"				,		UpperCamelCase__      :     Tuple=False				,		**UpperCamelCase__      :     Union[str, Any]				,		)				->					Optional[Any]:
								'''simple docstring'''







								UpperCAmelCase         =     AddedToken(UpperCamelCase__				,		lstrip=UpperCamelCase__				,		rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__				,		UpperCamelCase__      ) else bos_token
								UpperCAmelCase         =     AddedToken(UpperCamelCase__				,		lstrip=UpperCamelCase__				,		rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__				,		UpperCamelCase__      ) else eos_token
								UpperCAmelCase         =     AddedToken(UpperCamelCase__				,		lstrip=UpperCamelCase__				,		rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__				,		UpperCamelCase__      ) else sep_token
								UpperCAmelCase         =     AddedToken(UpperCamelCase__				,		lstrip=UpperCamelCase__				,		rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__				,		UpperCamelCase__      ) else cls_token
								UpperCAmelCase         =     AddedToken(UpperCamelCase__				,		lstrip=UpperCamelCase__				,		rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__				,		UpperCamelCase__      ) else unk_token
								UpperCAmelCase         =     AddedToken(UpperCamelCase__				,		lstrip=UpperCamelCase__				,		rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__				,		UpperCamelCase__      ) else pad_token

								# Mask token behave like a normal word, i.e. include the space before it
								UpperCAmelCase         =     AddedToken(UpperCamelCase__				,		lstrip=UpperCamelCase__				,		rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__				,		UpperCamelCase__      ) else mask_token

								super().__init__(
								    errors=UpperCamelCase__				,		bos_token=UpperCamelCase__				,		eos_token=UpperCamelCase__				,		unk_token=UpperCamelCase__				,		sep_token=UpperCamelCase__				,		cls_token=UpperCamelCase__				,		pad_token=UpperCamelCase__				,		mask_token=UpperCamelCase__				,		add_prefix_space=UpperCamelCase__				,		**UpperCamelCase__				,		)

								with open(UpperCamelCase__				,		encoding="utf-8"      ) as vocab_handle:
														UpperCAmelCase         =     json.load(UpperCamelCase__      )
								UpperCAmelCase         =     {v: k for k, v in self.encoder.items()}
								UpperCAmelCase         =     errors  # how to handle errors in decoding
								UpperCAmelCase         =     bytes_to_unicode()
								UpperCAmelCase         =     {v: k for k, v in self.byte_encoder.items()}
								with open(UpperCamelCase__				,		encoding="utf-8"      ) as merges_handle:
														UpperCAmelCase         =     merges_handle.read().split("\n"      )[1:-1]
								UpperCAmelCase         =     [tuple(merge.split()      ) for merge in bpe_merges]
								UpperCAmelCase         =     dict(zip(UpperCamelCase__				,		range(len(UpperCamelCase__      )      )      )      )
								UpperCAmelCase         =     {}
								UpperCAmelCase         =     add_prefix_space

								# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
								UpperCAmelCase         =     re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"      )






		@property
		# Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[int]      )				->					Union[str, Any]:
								'''simple docstring'''







								return len(self.encoder      )






		def SCREAMING_SNAKE_CASE_			(						self      :     int      )				->					Union[str, Any]:
								'''simple docstring'''







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






		def SCREAMING_SNAKE_CASE_			(						self      :     Union[str, Any]				,		UpperCamelCase__      :     Tuple      )				->					Union[str, Any]:
								'''simple docstring'''







								if token in self.cache:
														return self.cache[token]
								UpperCAmelCase         =     tuple(UpperCamelCase__      )
								UpperCAmelCase         =     get_pairs(UpperCamelCase__      )

								if not pairs:
														return token

								while True:
														UpperCAmelCase         =     min(UpperCamelCase__				,		key=lambda UpperCamelCase__      : self.bpe_ranks.get(UpperCamelCase__				,		float("inf"      )      )      )
														if bigram not in self.bpe_ranks:
																				break
														UpperCAmelCase       ,		UpperCAmelCase         =     bigram
														UpperCAmelCase         =     []
														UpperCAmelCase         =     0
														while i < len(UpperCamelCase__      ):
																				try:
																										UpperCAmelCase         =     word.index(UpperCamelCase__				,		UpperCamelCase__      )
																				except ValueError:
																										new_word.extend(word[i:]      )
																										break
																				else:
																										new_word.extend(word[i:j]      )
																										UpperCAmelCase         =     j

																				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
														UpperCAmelCase         =     tuple(UpperCamelCase__      )
														UpperCAmelCase         =     new_word
														if len(UpperCamelCase__      ) == 1:
																				break
														else:
																				UpperCAmelCase         =     get_pairs(UpperCamelCase__      )
								UpperCAmelCase         =     " ".join(UpperCamelCase__      )
								UpperCAmelCase         =     word
								return word






		def SCREAMING_SNAKE_CASE_			(						self      :     List[Any]				,		UpperCamelCase__      :     Tuple      )				->					int:
								'''simple docstring'''







								UpperCAmelCase         =     []
								for token in re.findall(self.pat				,		UpperCamelCase__      ):
														UpperCAmelCase         =     "".join(
														    self.byte_encoder[b] for b in token.encode("utf-8"      )      )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
														bpe_tokens.extend(bpe_token for bpe_token in self.bpe(UpperCamelCase__      ).split(" "      )      )
								return bpe_tokens






		def SCREAMING_SNAKE_CASE_			(						self      :     int				,		UpperCamelCase__      :     Tuple      )				->					List[str]:
								'''simple docstring'''







								return self.encoder.get(UpperCamelCase__				,		self.encoder.get(self.unk_token      )      )






		def SCREAMING_SNAKE_CASE_			(						self      :     List[str]				,		UpperCamelCase__      :     Optional[Any]      )				->					Dict:
								'''simple docstring'''







								return self.decoder.get(UpperCamelCase__      )






		def SCREAMING_SNAKE_CASE_			(						self      :     str				,		UpperCamelCase__      :     Tuple      )				->					List[str]:
								'''simple docstring'''







								UpperCAmelCase         =     "".join(UpperCamelCase__      )
								UpperCAmelCase         =     bytearray([self.byte_decoder[c] for c in text]      ).decode("utf-8"				,		errors=self.errors      )
								return text






		def SCREAMING_SNAKE_CASE_			(						self      :     str				,		UpperCamelCase__      :     str				,		UpperCamelCase__      :     Optional[str] = None      )				->					Tuple[str]:
								'''simple docstring'''







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

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

								return vocab_file, merge_file






		def SCREAMING_SNAKE_CASE_			(						self      :     Dict				,		UpperCamelCase__      :     List[int]				,		UpperCamelCase__      :     Optional[List[int]] = None				,		UpperCamelCase__      :     bool = False      )				->					List[int]:
								'''simple docstring'''







								if already_has_special_tokens:
														return super().get_special_tokens_mask(
														    token_ids_a=UpperCamelCase__				,		token_ids_a=UpperCamelCase__				,		already_has_special_tokens=UpperCamelCase__      )

								if token_ids_a is None:
														return [1] + ([0] * len(UpperCamelCase__      )) + [1]
								return [1] + ([0] * len(UpperCamelCase__      )) + [1, 1] + ([0] * len(UpperCamelCase__      )) + [1]






		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[Any]				,		UpperCamelCase__      :     List[int]				,		UpperCamelCase__      :     Optional[List[int]] = None      )				->					List[int]:
								'''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]






		def SCREAMING_SNAKE_CASE_			(						self      :     List[str]				,		UpperCamelCase__      :     str				,		UpperCamelCase__      :     Any=False				,		**UpperCamelCase__      :     Dict      )				->					Any:
								'''simple docstring'''







								UpperCAmelCase         =     kwargs.pop("add_prefix_space"				,		self.add_prefix_space      )
								if (is_split_into_words or add_prefix_space) and (len(UpperCamelCase__      ) > 0 and not text[0].isspace()):
														UpperCAmelCase         =     " " + text
								return (text, kwargs)






		def SCREAMING_SNAKE_CASE_			(						self      :     Dict				,		UpperCamelCase__      :     List[int]				,		UpperCamelCase__      :     Optional[List[int]] = None      )				->					Tuple:
								'''simple docstring'''







								return token_ids_a + [self.eos_token_id]







		def SCREAMING_SNAKE_CASE_			(						self      :     List[Any]				,		UpperCamelCase__      :     "Conversation"      )				->					List[int]:
								'''simple docstring'''







								UpperCAmelCase         =     []
								for is_user, text in conversation.iter_texts():
														if is_user:
																				# We need to space prefix as it's being done within blenderbot
																				inputs.append(" " + text      )
														else:
																				# Generated responses should contain them already.
																				inputs.append(UpperCamelCase__      )

								UpperCAmelCase         =     "  ".join(UpperCamelCase__      )
								UpperCAmelCase         =     self.encode(UpperCamelCase__      )
								if len(UpperCamelCase__      ) > self.model_max_length:
														UpperCAmelCase         =     input_ids[-self.model_max_length :]
														logger.warning(F'Trimmed input from conversation as it was longer than {self.model_max_length} tokens.'      )
								return input_ids








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__lowerCamelCase     :							Any  							=				{
    "configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase     :							Optional[int]  							=				[
		    "MEGA_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "MegaForCausalLM",
		    "MegaForMaskedLM",
		    "MegaForMultipleChoice",
		    "MegaForQuestionAnswering",
		    "MegaForSequenceClassification",
		    "MegaForTokenClassification",
		    "MegaModel",
		    "MegaPreTrainedModel",
		]

if TYPE_CHECKING:
		from .configuration_mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig, MegaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mega import (
				    MEGA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MegaForCausalLM,
				    MegaForMaskedLM,
				    MegaForMultipleChoice,
				    MegaForQuestionAnswering,
				    MegaForSequenceClassification,
				    MegaForTokenClassification,
				    MegaModel,
				    MegaPreTrainedModel,
				)

else:
		import sys

		__lowerCamelCase     :							int  							=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



