






'''simple docstring'''

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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
						from .tokenization_barthez import BarthezTokenizer
else:
						A:      str  				=				None

A:      Optional[Any]  				=				logging.get_logger(__name__)

A:      Optional[int]  				=				{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

A:      int  				=				{
    "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"
        ),
    },
    "tokenizer_file": {
        "moussaKam/mbarthez": "https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json",
        "moussaKam/barthez": "https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json",
        "moussaKam/barthez-orangesum-title": (
            "https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json"
        ),
    },
}

A:      Dict  				=				{
    "moussaKam/mbarthez": 1_0_2_4,
    "moussaKam/barthez": 1_0_2_4,
    "moussaKam/barthez-orangesum-title": 1_0_2_4,
}

A:      List[str]  				=				"▁"






class 							__magic_name__     (	__UpperCAmelCase				):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_					:      List[Any]        =  VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE_					:      Optional[int]        =  PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE_					:      int        =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	SCREAMING_SNAKE_CASE_					:      Optional[int]        =  ["input_ids", "attention_mask"]
	SCREAMING_SNAKE_CASE_					:      int        =  BarthezTokenizer
	def __init__(							self  ,      _lowercase=None  ,      _lowercase=None  ,      _lowercase="<s>"  ,      _lowercase="</s>"  ,      _lowercase="</s>"  ,      _lowercase="<s>"  ,      _lowercase="<unk>"  ,      _lowercase="<pad>"  ,      _lowercase="<mask>"  ,      **_lowercase  ,      )						->  Dict:
							# Mask token behave like a normal word, i.e. include the space before it
							lowercase_      :   str        =			AddedToken(_lowerCamelCase  ,      lstrip=_lowerCamelCase  ,      rstrip=_lowerCamelCase       ) if isinstance(_lowerCamelCase  ,      _lowerCamelCase       ) else mask_token

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

							lowercase_      :   Union[str, Any]        =			vocab_file
							lowercase_      :   List[str]        =			False if not self.vocab_file else True
	def        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase = None       )						->  Optional[int]:

							if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							lowercase_      :   Optional[Any]        =			[self.cls_token_id]
							lowercase_      :   Optional[int]        =			[self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep
	def        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase = None       )						->  Union[str, Any]:
							lowercase_      :   Optional[int]        =			[self.sep_token_id]
							lowercase_      :   Any        =			[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        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase = None       )						->  Optional[int]:
							if not self.can_save_slow_tokenizer:
													raise ValueError(
													    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
													    'tokenizer.'       )

							if not os.path.isdir(_lowerCamelCase       ):
													logger.error(f"Vocabulary path ({save_directory}) should be a directory"       )
													return
							lowercase_      :   str        =			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       ):
													copyfile(self.vocab_file  ,      _lowerCamelCase       )

							return (out_vocab_file,)








'''simple docstring'''

def 	_UpperCAmelCase    (  a		:	list[list[float]]							)			->			list[list[float]]:





						"""simple docstring"""
						lowercase_      :   list[list[float]]        =			[]
						for data in source_data:
												for i, el in enumerate(a							):
																		if len(a							) < i + 1:
																								data_lists.append([]							)
																		data_lists[i].append(float(a							)							)
						return data_lists






def 	_UpperCAmelCase    (  a		:	list[list[float]]						,			a		:	list[int]							)			->			list[list[float]]:





						"""simple docstring"""
						lowercase_      :   list[list[float]]        =			[]
						for dlist, weight in zip(a						,			a							):
												lowercase_      :   Tuple        =			min(a							)
												lowercase_      :   Any        =			max(a							)

												lowercase_      :   list[float]        =			[]
												# for weight 0 score is 1 - actual score
												if weight == 0:
																		for item in dlist:
																								try:
																														score.append(1 - ((item - mind) / (maxd - mind))							)
																								except ZeroDivisionError:
																														score.append(1							)

												elif weight == 1:
																		for item in dlist:
																								try:
																														score.append((item - mind) / (maxd - mind)							)
																								except ZeroDivisionError:
																														score.append(0							)

        # weight not 0 or 1
												else:
																		lowercase_      :   str        =			f"Invalid weight of {weight:f} provided"
																		raise ValueError(a							)

												score_lists.append(a							)

						return score_lists






def 	_UpperCAmelCase    (  a		:	list[list[float]]							)			->			list[float]:





						"""simple docstring"""
						lowercase_      :   list[float]        =			[0 for i in range(len(score_lists[0]							)							)]

						for slist in score_lists:
												for j, ele in enumerate(a							):
																		lowercase_      :   List[Any]        =			final_scores[j] + ele

						return final_scores






def 	_UpperCAmelCase    (  a		:	list[list[float]]						,			a		:	list[int]							)			->			list[list[float]]:





						"""simple docstring"""
						lowercase_      :   int        =			get_data(a							)
						lowercase_      :   Optional[int]        =			calculate_each_score(a						,			a							)
						lowercase_      :   Dict        =			generate_final_scores(a							)

						# append scores to source data
						for i, ele in enumerate(a							):
												source_data[i].append(a							)

						return source_data
