

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			     =       logging.get_logger(__name__)

__lowerCAmelCase			     =       {'vocab_file': 'spiece.model'}

__lowerCAmelCase			     =       {
    'vocab_file': {
        'bert_for_seq_generation': (
            'https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model'
        ),
    }
}

__lowerCAmelCase			     =       {'bert_for_seq_generation': 5_1_2}


class 			lowerCamelCase_    (  A__		):
							__lowercase				:	str        =				VOCAB_FILES_NAMES
							__lowercase				:	Any        =				PRETRAINED_VOCAB_FILES_MAP
							__lowercase				:	Optional[Any]        =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__lowercase				:	List[str]        =				[]
							__lowercase				:	Any        =				["input_ids", "attention_mask"]


							def __init__( self      ,				lowerCamelCase_      ,				lowerCamelCase_="<s>"      ,				lowerCamelCase_="</s>"      ,				lowerCamelCase_="<unk>"      ,				lowerCamelCase_="<pad>"      ,				lowerCamelCase_="<::::>"      ,				lowerCamelCase_ = None      ,				**lowerCamelCase_      ,				)							->   Any:



								"""simple docstring"""

								_UpperCamelCase			=   {} if sp_model_kwargs is None else sp_model_kwargs

								# Add extra_ids to the special token list
								super().__init__(
								    bos_token=lowerCamelCase_      ,				eos_token=lowerCamelCase_      ,				unk_token=lowerCamelCase_      ,				pad_token=lowerCamelCase_      ,				sep_token=lowerCamelCase_      ,				sp_model_kwargs=self.sp_model_kwargs      ,				**lowerCamelCase_      ,				)

								_UpperCamelCase			=   vocab_file

								_UpperCamelCase			=   spm.SentencePieceProcessor(**self.sp_model_kwargs						)
								self.sp_model.Load(lowerCamelCase_						)


							@property
							def  lowercase   ( self						)							->   Union[str, Any]:



								"""simple docstring"""

								return self.sp_model.get_piece_size()


							def  lowercase   ( self						)							->   Any:



								"""simple docstring"""

								_UpperCamelCase			=   {self.convert_ids_to_tokens(lowerCamelCase_						): i for i in range(self.vocab_size						)}
								vocab.update(self.added_tokens_encoder						)
								return vocab


							def __getstate__( self						)							->   List[Any]:



								"""simple docstring"""

								_UpperCamelCase			=   self.__dict__.copy()
								_UpperCamelCase			=   None
								return state


							def __setstate__( self      ,				lowerCamelCase_						)							->   Any:



								"""simple docstring"""

								_UpperCamelCase			=   d

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

								_UpperCamelCase			=   spm.SentencePieceProcessor(**self.sp_model_kwargs						)
								self.sp_model.Load(self.vocab_file						)


							def  lowercase   ( self      ,				lowerCamelCase_						)							->   Any:



								"""simple docstring"""

								return self.sp_model.encode(lowerCamelCase_      ,				out_type=lowerCamelCase_						)


							def  lowercase   ( self      ,				lowerCamelCase_						)							->   List[str]:



								"""simple docstring"""

								return self.sp_model.piece_to_id(lowerCamelCase_						)


							def  lowercase   ( self      ,				lowerCamelCase_						)							->   List[Any]:



								"""simple docstring"""

								_UpperCamelCase			=   self.sp_model.IdToPiece(lowerCamelCase_						)
								return token


							def  lowercase   ( self      ,				lowerCamelCase_						)							->   int:



								"""simple docstring"""

								_UpperCamelCase			=   []
								_UpperCamelCase			=   ""
								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(lowerCamelCase_						) + token
										_UpperCamelCase			=   []
									else:
										current_sub_tokens.append(lowerCamelCase_						)
								out_string += self.sp_model.decode(lowerCamelCase_						)
								return out_string.strip()







							def  lowercase   ( self      ,				lowerCamelCase_      ,				lowerCamelCase_ = None						)							->   Tuple:



								"""simple docstring"""

								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"]						)

								if os.path.abspath(self.vocab_file						) != os.path.abspath(lowerCamelCase_						) and os.path.isfile(self.vocab_file						):
									copyfile(self.vocab_file      ,				lowerCamelCase_						)
								elif not os.path.isfile(self.vocab_file						):
									with open(lowerCamelCase_      ,				"wb"						) as fi:
										_UpperCamelCase			=   self.sp_model.serialized_model_proto()
										fi.write(lowerCamelCase_						)

								return (out_vocab_file,)












import sys
import turtle






def     a     (		lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2






def     a     (		lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  ):






				'''simple docstring'''
				my_pen.up()
				my_pen.goto(vertexa[0]						,  vertexa[1]							)
				my_pen.down()
				my_pen.goto(vertexa[0]						,  vertexa[1]							)
				my_pen.goto(vertexa[0]						,  vertexa[1]							)
				my_pen.goto(vertexa[0]						,  vertexa[1]							)

				if depth == 0:
								return

				triangle(lowerCamelCase_						,  get_mid(lowerCamelCase_						,  lowerCamelCase_							)						,  get_mid(lowerCamelCase_						,  lowerCamelCase_							)						,  depth - 1							)
				triangle(lowerCamelCase_						,  get_mid(lowerCamelCase_						,  lowerCamelCase_							)						,  get_mid(lowerCamelCase_						,  lowerCamelCase_							)						,  depth - 1							)
				triangle(lowerCamelCase_						,  get_mid(lowerCamelCase_						,  lowerCamelCase_							)						,  get_mid(lowerCamelCase_						,  lowerCamelCase_							)						,  depth - 1							)


if __name__ == "__main__":
							if len(sys.argv) != 2:
														raise ValueError(
														    'Correct format for using this script: '
														    'python fractals.py <int:depth_for_fractal>'
														)
							A__      :     Dict       =					turtle.Turtle()
							my_pen.ht()
							my_pen.speed(5)
							my_pen.pencolor('red')

							A__      :     Union[str, Any]       =					[(-1_75, -1_25), (0, 1_75), (1_75, -1_25)]  # vertices of triangle
							triangle(vertices[0], vertices[1], vertices[2], int(sys.argv[1]))




