






"""simple docstring"""







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


a			:    Optional[Any]				 =		"▁"

a			:    Dict				 =		{"vocab_file": "spiece.model"}

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

a			:    Optional[int]				 =		{
    "google/pegasus-xsum": 512,
}


a			:    Dict				 =		logging.get_logger(__name__)


class    __UpperCAmelCase(       _UpperCAmelCase							):




						"""simple docstring"""




						__lowerCamelCase    	= VOCAB_FILES_NAMES

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




						def __init__(       self	,  snake_case__	,  snake_case__="<pad>"	,  snake_case__="</s>"	,  snake_case__="<unk>"	,  snake_case__="<mask_2>"	,  snake_case__="<mask_1>"	,  snake_case__=None	,  snake_case__=103	,  snake_case__ = None	,  **snake_case__	,  ):
												'''simple docstring'''
												lowercase__    :				Optional[Any]=	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__    :				Optional[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__    :				str=	additional_special_tokens_extended
												else:
																		lowercase__    :				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__    :				Tuple=	{} 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__    :				Any=	mask_token_sent
												lowercase__    :				Any=	vocab_file
												lowercase__    :				Optional[int]=	spm.SentencePieceProcessor(**self.sp_model_kwargs      )
												self.sp_model.Load(lowercase_      )

												# add special tokens to encoder dict
												lowercase__    :				Dict[int, str]=	{
												    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__    :				Dict[str, int]=	{v: k for k, v in self.encoder.items()}




						@property
						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												return len(self.sp_model      ) + self.offset




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												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      ):
												'''simple docstring'''
												lowercase__    :				str=	self.__dict__.copy()
												lowercase__    :				int=	None
												return state




						def __setstate__(       self	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				int=	d

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

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




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												return self.sp_model.encode(lowercase_	,  out_type=lowercase_      )




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												if token in self.decoder:
																		return self.decoder[token]
												elif token in self.added_tokens_decoder:
																		return self.added_tokens_decoder[token]
												lowercase__    :				str=	self.sp_model.piece_to_id(lowercase_      )
												return sp_id + self.offset




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												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[str]=	self.sp_model.IdToPiece(index - self.offset      )
												return token




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				int=	[]
												lowercase__    :				int=	""""""
												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__    :				List[str]=	[]
																		else:
																								current_sub_tokens.append(lowercase_      )
												out_string += self.sp_model.decode(lowercase_      )
												return out_string.strip()




						def 		UpperCAmelCase_	(       self	,  snake_case__=False      ):
												'''simple docstring'''
												return 1




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				Union[str, Any]=	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 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__ = None	,  snake_case__ = False      ):
												'''simple docstring'''
												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 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__=None      ):
												'''simple docstring'''
												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 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__ = None      ):
												'''simple docstring'''
												if not os.path.isdir(lowercase_      ):
																		logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
																		return
												lowercase__    :				Optional[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__    :				Dict=	self.sp_model.serialized_model_proto()
																								fi.write(lowercase_      )

												return (out_vocab_file,)














"""simple docstring"""







from __future__ import annotations





def 						lowercase__(A ,		A						)    ->list[str]:




						"""simple docstring"""



						if partitions <= 0:
												raise ValueError("partitions must be a positive number!"						)
						if partitions > number_of_bytes:
												raise ValueError("partitions can not > number_of_bytes!"						)
						lowercase__    :				List[str]=	number_of_bytes // partitions
						lowercase__    :				Dict=	[]
						for i in range(A						):
												lowercase__    :				Union[str, Any]=	i * bytes_per_partition + 1
												lowercase__    :				Any=	(
												    number_of_bytes if i == partitions - 1 else (i + 1) * bytes_per_partition
												)
												allocation_list.append(f'''{start_bytes}-{end_bytes}'''						)
						return allocation_list


if __name__ == "__main__":
			import doctest

			doctest.testmod()






