





'''simple docstring'''



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

import sentencepiece as spm

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


_SCREAMING_SNAKE_CASE					=    logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE					=    {'''vocab_file''': '''sentencepiece.bpe.model'''}

_SCREAMING_SNAKE_CASE					=    {
    '''vocab_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'''
        ),
    },
}

_SCREAMING_SNAKE_CASE					=    {
    '''moussaKam/mbarthez''': 1_0_2_4,
    '''moussaKam/barthez''': 1_0_2_4,
    '''moussaKam/barthez-orangesum-title''': 1_0_2_4,
}

_SCREAMING_SNAKE_CASE					=    '''▁'''






class 							__lowercase       (      lowerCAmelCase__						):







	'''simple docstring'''

	a    :				Tuple											=       VOCAB_FILES_NAMES
	a    :				List[Any]											=       PRETRAINED_VOCAB_FILES_MAP
	a    :				str											=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	a    :				Union[str, Any]											=       ["input_ids", "attention_mask"]


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







				'''simple docstring'''





				__lowercase										=							AddedToken(_lowerCamelCase     ,lstrip=_lowerCamelCase     ,rstrip=_lowerCamelCase ) if isinstance(_lowerCamelCase     ,_lowerCamelCase ) else mask_token

				__lowercase										=							{} if sp_model_kwargs is None else sp_model_kwargs

				super().__init__(
				    bos_token=_lowerCamelCase     ,eos_token=_lowerCamelCase     ,unk_token=_lowerCamelCase     ,sep_token=_lowerCamelCase     ,cls_token=_lowerCamelCase     ,pad_token=_lowerCamelCase     ,mask_token=_lowerCamelCase     ,sp_model_kwargs=self.sp_model_kwargs     ,**_lowerCamelCase     ,)

				__lowercase										=							vocab_file
				__lowercase										=							spm.SentencePieceProcessor(**self.sp_model_kwargs )
				self.sp_model.Load(str(_lowerCamelCase ) )

				__lowercase										=							{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

				__lowercase										=							len(self.sp_model ) - 1
				__lowercase										=							{v: k for k, v in self.fairseq_tokens_to_ids.items()}


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase     ,_lowerCamelCase = None )							->							List[int]:







				'''simple docstring'''





				if token_ids_a is None:
							return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
				__lowercase										=							[self.cls_token_id]
				__lowercase										=							[self.sep_token_id]
				return cls + token_ids_a + sep + sep + token_ids_a + sep


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase     ,_lowerCamelCase = None     ,_lowerCamelCase = False )							->							List[int]:







				'''simple docstring'''





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

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


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase     ,_lowerCamelCase = None )							->							List[int]:







				'''simple docstring'''





				__lowercase										=							[self.sep_token_id]
				__lowercase										=							[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]


	@property
	def 						_UpperCAmelCase     (self )							->							Any:







				'''simple docstring'''





				return len(self.sp_model )


	def 						_UpperCAmelCase     (self )							->							str:







				'''simple docstring'''





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


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase )							->							List[str]:







				'''simple docstring'''





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


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase )							->							Optional[Any]:







				'''simple docstring'''





				if token in self.fairseq_tokens_to_ids:
							return self.fairseq_tokens_to_ids[token]
				__lowercase										=							self.sp_model.PieceToId(_lowerCamelCase )

				return spm_id if spm_id else self.unk_token_id


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase )							->							Optional[int]:







				'''simple docstring'''





				if index in self.fairseq_ids_to_tokens:
							return self.fairseq_ids_to_tokens[index]
				return self.sp_model.IdToPiece(_lowerCamelCase )


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase )							->							Tuple:







				'''simple docstring'''





				__lowercase										=							[]
				__lowercase										=							''''''
				__lowercase										=							False
				for token in tokens:
							# make sure that special tokens are not decoded using sentencepiece model
							if token in self.all_special_tokens:
										if not prev_is_special:
													out_string += " "
										out_string += self.sp_model.decode(_lowerCamelCase ) + token
										__lowercase										=							True
										__lowercase										=							[]
							else:
										current_sub_tokens.append(_lowerCamelCase )
										__lowercase										=							False
				out_string += self.sp_model.decode(_lowerCamelCase )
				return out_string.strip()


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







				'''simple docstring'''





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


	def __setstate__(self     ,_lowerCamelCase )							->							Optional[Any]:







				'''simple docstring'''





				__lowercase										=							d

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

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


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase     ,_lowerCamelCase = None )							->							Tuple[str]:







				'''simple docstring'''





				if not os.path.isdir(_lowerCamelCase ):
							logger.error(f"Vocabulary path ({save_directory}) should be a directory" )
							return
				__lowercase										=							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:
										__lowercase										=							self.sp_model.serialized_model_proto()
										fi.write(_lowerCamelCase )

				return (out_vocab_file,)












'''simple docstring'''



from __future__ import annotations

import time
from collections.abc import Sequence
from random import randint

from matplotlib import pyplot as plt




def    _lowerCAmelCase						(				lowerCamelCase_			:  Sequence[float]		,       lowerCamelCase_			:  int		,       lowerCamelCase_			:  int				):
			if not arr:
						return None, None, 0
			if low == high:
						return low, high, arr[low]

			__lowercase										=							(low + high) // 2
			__lowercase						,		__lowercase						,		__lowercase										=							max_subarray(lowerCamelCase_		,       lowerCamelCase_		,       lowerCamelCase_				)
			__lowercase						,		__lowercase						,		__lowercase										=							max_subarray(lowerCamelCase_		,       mid + 1		,       lowerCamelCase_				)
			__lowercase						,		__lowercase						,		__lowercase										=							max_cross_sum(lowerCamelCase_		,       lowerCamelCase_		,       lowerCamelCase_		,       lowerCamelCase_				)
			if left_sum >= right_sum and left_sum >= cross_sum:
						return left_low, left_high, left_sum
			elif right_sum >= left_sum and right_sum >= cross_sum:
						return right_low, right_high, right_sum
			return cross_left, cross_right, cross_sum




def    _lowerCAmelCase						(				lowerCamelCase_			:  Sequence[float]		,       lowerCamelCase_			:  int		,       lowerCamelCase_			:  int		,       lowerCamelCase_			:  int				):
			__lowercase						,		__lowercase										=							float('''-inf'''				), -1
			__lowercase						,		__lowercase										=							float('''-inf'''				), -1

			__lowercase										=							0
			for i in range(lowerCamelCase_		,       low - 1		,       -1				):
						summ += arr[i]
						if summ > left_sum:
									__lowercase										=							summ
									__lowercase										=							i

			__lowercase										=							0
			for i in range(mid + 1		,       high + 1				):
						summ += arr[i]
						if summ > right_sum:
									__lowercase										=							summ
									__lowercase										=							i

			return max_left, max_right, (left_sum + right_sum)




def    _lowerCAmelCase						(				lowerCamelCase_			:  int				):
			__lowercase										=							[randint(1		,       lowerCamelCase_				) for _ in range(lowerCamelCase_				)]
			__lowercase										=							time.time()
			max_subarray(lowerCamelCase_		,       0		,       input_size - 1				)
			__lowercase										=							time.time()
			return end - start




def    _lowerCAmelCase						(				):
			__lowercase										=							[1_0, 1_0_0, 1_0_0_0, 1_0_0_0_0, 5_0_0_0_0, 1_0_0_0_0_0, 2_0_0_0_0_0, 3_0_0_0_0_0, 4_0_0_0_0_0, 5_0_0_0_0_0]
			__lowercase										=							[time_max_subarray(lowerCamelCase_				) for input_size in input_sizes]
			print('''No of Inputs\t\tTime Taken'''				)
			for input_size, runtime in zip(lowerCamelCase_		,       lowerCamelCase_				):
						print(lowerCamelCase_		,       '''\t\t'''		,       lowerCamelCase_				)
			plt.plot(lowerCamelCase_		,       lowerCamelCase_				)
			plt.xlabel('''Number of Inputs'''				)
			plt.ylabel('''Time taken in seconds'''				)
			plt.show()


if __name__ == "__main__":
	from doctest import testmod

	testmod()





