



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

import sentencepiece as spm

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


lowerCAmelCase__	    =    "▁"

lowerCAmelCase__	    =    {"vocab_file": "spiece.model"}

lowerCAmelCase__	    =    {
    "vocab_file": {"google/pegasus-xsum": "https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model"}
}

lowerCAmelCase__	    =    {
    "google/pegasus-xsum": 5_1_2,
}


lowerCAmelCase__	    =    logging.get_logger(__name__)

class  snake_case__(lowercase_     ):

					"""simple docstring"""






					lowercase_								=						VOCAB_FILES_NAMES

					lowercase_								=						VOCAB_FILES_NAMES
					lowercase_								=						PRETRAINED_VOCAB_FILES_MAP
					lowercase_								=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase_								=						["""input_ids""", """attention_mask"""]







					def __init__(				self   :      Tuple ,  SCREAMING_SNAKE_CASE   :      Dict ,  SCREAMING_SNAKE_CASE   :      Optional[Any]="<pad>" ,  SCREAMING_SNAKE_CASE   :      Any="</s>" ,  SCREAMING_SNAKE_CASE   :      Optional[int]="<unk>" ,  SCREAMING_SNAKE_CASE   :      Optional[int]="<mask_2>" ,  SCREAMING_SNAKE_CASE   :      Any="<mask_1>" ,  SCREAMING_SNAKE_CASE   :      Optional[int]=None ,  SCREAMING_SNAKE_CASE   :      Union[str, Any]=103 ,  SCREAMING_SNAKE_CASE   :      Tuple = None ,  **SCREAMING_SNAKE_CASE   :      Optional[Any] ,  ):
									lowercase__	:       int						=	offset
									if additional_special_tokens is not None:
													if not isinstance(_lowercase ,  _lowercase	):
																	raise TypeError(
																	    f"""additional_special_tokens should be of type {type(_lowercase	)}, but is"""
																	    f""" {type(_lowercase	)}"""	)

													lowercase__	:       Any						=	(
													    ([mask_token_sent] + additional_special_tokens)
													    if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
													    else additional_special_tokens
													)
													# fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
													additional_special_tokens_extended += [
													    f"""<unk_{i}>""" for i in range(len(_lowercase	) ,  self.offset - 1	)
													]

													if len(set(_lowercase	)	) != len(_lowercase	):
																	raise ValueError(
																	    "Please make sure that the provided additional_special_tokens do not contain an incorrectly"
																	    f""" shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}."""	)
													lowercase__	:       Union[str, Any]						=	additional_special_tokens_extended
									else:
													lowercase__	:       Optional[int]						=	[mask_token_sent] if mask_token_sent is not None else []
													additional_special_tokens += [f"""<unk_{i}>""" for i in range(2 ,  self.offset	)]

									lowercase__	:       Any						=	{} if sp_model_kwargs is None else sp_model_kwargs

									super().__init__(
									    eos_token=_lowercase ,  unk_token=_lowercase ,  mask_token=_lowercase ,  pad_token=_lowercase ,  mask_token_sent=_lowercase ,  offset=_lowercase ,  additional_special_tokens=_lowercase ,  sp_model_kwargs=self.sp_model_kwargs ,  **_lowercase ,  )
									lowercase__	:       str						=	mask_token_sent
									lowercase__	:       Dict						=	vocab_file
									lowercase__	:       Any						=	spm.SentencePieceProcessor(**self.sp_model_kwargs	)
									self.sp_model.Load(_lowercase	)

									# add special tokens to encoder dict
									lowercase__	:       Tuple						=	{
									    0: self.pad_token,
									    1: self.eos_token,
									}

									if self.mask_token_sent is not None:
													self.encoder.update(
													    {
													        2: self.mask_token_sent,
													        3: self.mask_token,
													    }	)

									if self.offset > 0:
													# entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
													# mask_token_sent is already added to list -> so start at 1
													self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1 ,  self.offset - 1	)}	)

									lowercase__	:       List[str]						=	{v: k for k, v in self.encoder.items()}







					@property
					def 					snake_case	(				self   :      Tuple	):
									return len(self.sp_model	) + self.offset







					def 					snake_case	(				self   :      str	):
									lowercase__	:       int						=	{self.convert_ids_to_tokens(_lowercase	): i for i in range(self.vocab_size	)}
									vocab.update(self.added_tokens_encoder	)
									return vocab







					def __getstate__(				self   :      List[Any]	):
									lowercase__	:       Optional[Any]						=	self.__dict__.copy()
									lowercase__	:       Any						=	None
									return state







					def __setstate__(				self   :      int ,  SCREAMING_SNAKE_CASE   :      str	):
									lowercase__	:       Optional[int]						=	d

									# for backward compatibility
									if not hasattr(self ,  "sp_model_kwargs"	):
													lowercase__	:       int						=	{}

									lowercase__	:       Optional[int]						=	spm.SentencePieceProcessor(**self.sp_model_kwargs	)
									self.sp_model.Load(self.vocab_file	)







					def 					snake_case	(				self   :      Dict ,  SCREAMING_SNAKE_CASE   :      Dict	):
									return self.sp_model.encode(_lowercase ,  out_type=_lowercase	)







					def 					snake_case	(				self   :      Optional[Any] ,  SCREAMING_SNAKE_CASE   :      Union[str, Any]	):
									if token in self.decoder:
													return self.decoder[token]
									elif token in self.added_tokens_decoder:
													return self.added_tokens_decoder[token]
									lowercase__	:       Any						=	self.sp_model.piece_to_id(_lowercase	)
									return sp_id + self.offset







					def 					snake_case	(				self   :      Optional[int] ,  SCREAMING_SNAKE_CASE   :      Optional[int]	):
									if index in self.encoder:
													return self.encoder[index]
									elif index in self.added_tokens_encoder:
													return self.added_tokens_encoder[index]
									else:
													lowercase__	:       List[Any]						=	self.sp_model.IdToPiece(index - self.offset	)
									return token







					def 					snake_case	(				self   :      List[Any] ,  SCREAMING_SNAKE_CASE   :      str	):
									lowercase__	:       List[str]						=	[]
									lowercase__	:       Dict						=	""
									for token in tokens:
													# make sure that special tokens are not decoded using sentencepiece model
													if token in self.all_special_tokens:
																	out_string += self.sp_model.decode(_lowercase	) + token
																	lowercase__	:       Tuple						=	[]
													else:
																	current_sub_tokens.append(_lowercase	)
									out_string += self.sp_model.decode(_lowercase	)
									return out_string.strip()







					def 					snake_case	(				self   :      str ,  SCREAMING_SNAKE_CASE   :      Optional[Any]=False	):
									return 1







					def 					snake_case	(				self   :      str ,  SCREAMING_SNAKE_CASE   :      Dict	):
									lowercase__	:       List[str]						=	set(self.all_special_ids	)  # call it once instead of inside list comp
									all_special_ids.remove(self.unk_token_id	)  # <unk> is only sometimes special

									return [1 if x in all_special_ids else 0 for x in seq]







					def 					snake_case	(				self   :      Tuple ,  SCREAMING_SNAKE_CASE   :      Union[str, Any] ,  SCREAMING_SNAKE_CASE   :      Dict = None ,  SCREAMING_SNAKE_CASE   :      Any = False	):
									if already_has_special_tokens:
													return self._special_token_mask(_lowercase	)
									elif token_ids_a is None:
													return self._special_token_mask(_lowercase	) + [1]
									else:
													return self._special_token_mask(token_ids_a + token_ids_a	) + [1]







					def 					snake_case	(				self   :      Tuple ,  SCREAMING_SNAKE_CASE   :      List[Any] ,  SCREAMING_SNAKE_CASE   :      Dict=None	):
									if token_ids_a is None:
													return token_ids_a + [self.eos_token_id]
									# We don't expect to process pairs, but leave the pair logic for API consistency
									return token_ids_a + token_ids_a + [self.eos_token_id]







					def 					snake_case	(				self   :      List[str] ,  SCREAMING_SNAKE_CASE   :      Dict ,  SCREAMING_SNAKE_CASE   :      List[Any] = None	):
									if not os.path.isdir(_lowercase	):
													logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
													return
									lowercase__	:       List[Any]						=	os.path.join(
									    _lowercase ,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]	)

									if os.path.abspath(self.vocab_file	) != os.path.abspath(_lowercase	) and os.path.isfile(self.vocab_file	):
													copyfile(self.vocab_file ,  _lowercase	)
									elif not os.path.isfile(self.vocab_file	):
													with open(_lowercase ,  "wb"	) as fi:
																	lowercase__	:       Optional[int]						=	self.sp_model.serialized_model_proto()
																	fi.write(_lowercase	)

									return (out_vocab_file,)







'''simple docstring'''

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_bart import BartTokenizer


SCREAMING_SNAKE_CASE							:				int     	=			logging.get_logger(__name__)


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

# See all BART models at https://huggingface.co/models?filter=bart
SCREAMING_SNAKE_CASE							:				str     	=			{
    "vocab_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/vocab.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/vocab.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json",
    },
    "merges_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/merges.txt",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/merges.txt",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json",
    },
}

SCREAMING_SNAKE_CASE							:				Union[str, Any]     	=			{
    "facebook/bart-base": 1024,
    "facebook/bart-large": 1024,
    "facebook/bart-large-mnli": 1024,
    "facebook/bart-large-cnn": 1024,
    "facebook/bart-large-xsum": 1024,
    "yjernite/bart_eli5": 1024,
}






class    snake_case     (      lowercase_		):






				"""simple docstring"""
				_a    	=     VOCAB_FILES_NAMES
				_a    	=     PRETRAINED_VOCAB_FILES_MAP
				_a    	=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_a    	=     ["""input_ids""", """attention_mask"""]
				_a    	=     BartTokenizer



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

											SCREAMING_SNAKE_CASE_				=				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()       )
											if pre_tok_state.get('add_prefix_space',     _lowercase       ) != add_prefix_space:
																		SCREAMING_SNAKE_CASE_				=				getattr(_lowercase,     pre_tok_state.pop('type'       )       )
																		SCREAMING_SNAKE_CASE_				=				add_prefix_space
																		SCREAMING_SNAKE_CASE_				=				pre_tok_class(**_lowercase       )

											SCREAMING_SNAKE_CASE_				=				add_prefix_space

											# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
											SCREAMING_SNAKE_CASE_				=				'post_processor'
											SCREAMING_SNAKE_CASE_				=				getattr(self.backend_tokenizer,     _lowercase,     _lowercase       )
											if tokenizer_component_instance:
																		SCREAMING_SNAKE_CASE_				=				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:
																									SCREAMING_SNAKE_CASE_				=				tuple(state['sep']       )
																		if "cls" in state:
																									SCREAMING_SNAKE_CASE_				=				tuple(state['cls']       )

																		SCREAMING_SNAKE_CASE_				=				False

																		if state.get('add_prefix_space',     _lowercase       ) != add_prefix_space:
																									SCREAMING_SNAKE_CASE_				=				add_prefix_space
																									SCREAMING_SNAKE_CASE_				=				True

																		if state.get('trim_offsets',     _lowercase       ) != trim_offsets:
																									SCREAMING_SNAKE_CASE_				=				trim_offsets
																									SCREAMING_SNAKE_CASE_				=				True

																		if changes_to_apply:
																									SCREAMING_SNAKE_CASE_				=				getattr(_lowercase,     state.pop('type'       )       )
																									SCREAMING_SNAKE_CASE_				=				component_class(**_lowercase       )
																									setattr(self.backend_tokenizer,     _lowercase,     _lowercase       )



				@property
				def   a__					(    self       )     ->							str:
											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   a__					(    self,     _lowercase       )     ->							Dict:
											SCREAMING_SNAKE_CASE_				=				AddedToken(_lowercase,     lstrip=_lowercase,     rstrip=_lowercase       ) if isinstance(_lowercase,     _lowercase       ) else value
											SCREAMING_SNAKE_CASE_				=				value



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							BatchEncoding:
											SCREAMING_SNAKE_CASE_				=				kwargs.get('is_split_into_words',     _lowercase       )

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.'       )

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



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							BatchEncoding:
											SCREAMING_SNAKE_CASE_				=				kwargs.get('is_split_into_words',     _lowercase       )

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.'       )

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



				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							Tuple[str]:
											SCREAMING_SNAKE_CASE_				=				self._tokenizer.model.save(_lowercase,     name=_lowercase       )
											return tuple(_lowercase       )



				def   a__					(    self,     _lowercase,     _lowercase=None       )     ->							Optional[Any]:
											SCREAMING_SNAKE_CASE_				=				[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   a__					(    self,     _lowercase,     _lowercase = None       )     ->							List[int]:
											SCREAMING_SNAKE_CASE_				=				[self.sep_token_id]
											SCREAMING_SNAKE_CASE_				=				[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]





