
"""simple docstring"""





from __future__ import annotations
def 				A_  (__a					):

					'''simple docstring'''





					A_								=    0.00
					A_								=    0
					for resistor in resistors:
										if resistor <= 0:
															A_								=    f'Resistor at index {index} has a negative or zero value!'
															raise ValueError(__a					)
										first_sum += 1 / float(__a					)
										index += 1
					return 1 / first_sum
def 				A_  (__a					):

					'''simple docstring'''





					A_								=    0.00
					A_								=    0
					for resistor in resistors:
										sum_r += resistor
										if resistor < 0:
															A_								=    f'Resistor at index {index} has a negative value!'
															raise ValueError(__a					)
										index += 1
					return sum_r


if __name__ == "__main__":
		import doctest

		doctest.testmod()






"""simple docstring"""





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

from tokenizers import processors

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


if is_sentencepiece_available():
		from .tokenization_mbart import MBartTokenizer
else:
		UpperCamelCase_       :    Dict						      =			None


UpperCamelCase_       :    int						      =			logging.get_logger(__name__)


UpperCamelCase_       :    str						      =			{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCamelCase_       :    List[Any]						      =			{
    '''vocab_file''': {
        '''facebook/mbart-large-en-ro''': (
            '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'''
        ),
        '''facebook/mbart-large-cc25''': (
            '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/mbart-large-en-ro''': '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json''',
        '''facebook/mbart-large-cc25''': '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json''',
    },
}

UpperCamelCase_       :    Optional[Any]						      =			{
    '''facebook/mbart-large-en-ro''': 1024,
    '''facebook/mbart-large-cc25''': 1024,
}

# fmt: off
UpperCamelCase_       :    str						      =			['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''']



class __lowerCAmelCase					(       _lowercase   ):




			"""simple docstring"""







			snake_case						   =					VOCAB_FILES_NAMES
			snake_case						   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			snake_case						   =					PRETRAINED_VOCAB_FILES_MAP
			snake_case						   =					["input_ids", "attention_mask"]
			snake_case						   =					MBartTokenizer

			snake_case						   =					[]
			snake_case						   =					[]




			def __init__(					self    :       List[str]							, _snake_case    :       Tuple=None							, _snake_case    :       int=None							, _snake_case    :       List[Any]="<s>"							, _snake_case    :       Tuple="</s>"							, _snake_case    :       str="</s>"							, _snake_case    :       List[Any]="<s>"							, _snake_case    :       Dict="<unk>"							, _snake_case    :       str="<pad>"							, _snake_case    :       Any="<mask>"							, _snake_case    :       int=None							, _snake_case    :       Optional[int]=None							, _snake_case    :       Any=None							, **_snake_case    :       Union[str, Any]							, )   ->			List[str]:







								"""simple docstring"""
								# Mask token behave like a normal word, i.e. include the space before it
								A_								=    AddedToken(_snake_case							, lstrip=_snake_case							, rstrip=_snake_case						) if isinstance(_snake_case							, _snake_case						) else mask_token

								super().__init__(
								    vocab_file=_snake_case							, tokenizer_file=_snake_case							, bos_token=_snake_case							, eos_token=_snake_case							, sep_token=_snake_case							, cls_token=_snake_case							, unk_token=_snake_case							, pad_token=_snake_case							, mask_token=_snake_case							, src_lang=_snake_case							, tgt_lang=_snake_case							, additional_special_tokens=_snake_case							, **_snake_case							, )

								A_								=    vocab_file
								A_								=    False if not self.vocab_file else True

								A_								=    FAIRSEQ_LANGUAGE_CODES.copy()

								if additional_special_tokens is not None:
													# Only add those special tokens if they are not already there.
													_additional_special_tokens.extend(
													    [t for t in additional_special_tokens if t not in _additional_special_tokens]						)

								self.add_special_tokens({"additional_special_tokens": _additional_special_tokens}						)
								A_								=    {
								    lang_code: self.convert_tokens_to_ids(_snake_case						) for lang_code in FAIRSEQ_LANGUAGE_CODES
								}

								A_								=    src_lang if src_lang is not None else "en_XX"
								A_								=    self.convert_tokens_to_ids(self._src_lang						)
								A_								=    tgt_lang
								self.set_src_lang_special_tokens(self._src_lang						)




			@property
			def   lowerCamelCase__  (					self    :       Dict						)   ->			str:







								"""simple docstring"""
								return self._src_lang




			@src_lang.setter
			def   lowerCamelCase__  (					self    :       Tuple							, _snake_case    :       str						)   ->			None:







								"""simple docstring"""
								A_								=    new_src_lang
								self.set_src_lang_special_tokens(self._src_lang						)




			def   lowerCamelCase__  (					self    :       Optional[Any]							, _snake_case    :       List[int]							, _snake_case    :       Optional[List[int]] = None						)   ->			List[int]:







								"""simple docstring"""
								if token_ids_a is None:
													return self.prefix_tokens + token_ids_a + self.suffix_tokens
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens




			def   lowerCamelCase__  (					self    :       Dict							, _snake_case    :       List[int]							, _snake_case    :       Optional[List[int]] = None						)   ->			List[int]:







								"""simple docstring"""
								A_								=    [self.sep_token_id]
								A_								=    [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    :       List[Any]							, _snake_case    :       str							, _snake_case    :       str							, _snake_case    :       Optional[str]							, _snake_case    :       Optional[str]							, **_snake_case    :       Optional[int]						)   ->			str:







								"""simple docstring"""
								if src_lang is None or tgt_lang is None:
													raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"						)
								A_								=    src_lang
								A_								=    self(_snake_case							, add_special_tokens=_snake_case							, return_tensors=_snake_case							, **_snake_case						)
								A_								=    self.convert_tokens_to_ids(_snake_case						)
								A_								=    tgt_lang_id
								return inputs




			def   lowerCamelCase__  (					self    :       Dict							, _snake_case    :       List[str]							, _snake_case    :       str = "en_XX"							, _snake_case    :       Optional[List[str]] = None							, _snake_case    :       str = "ro_RO"							, **_snake_case    :       str							, )   ->			BatchEncoding:







								"""simple docstring"""
								A_								=    src_lang
								A_								=    tgt_lang
								return super().prepare_seqaseq_batch(_snake_case							, _snake_case							, **_snake_case						)




			def   lowerCamelCase__  (					self    :       Any						)   ->			Optional[Any]:







								"""simple docstring"""
								return self.set_src_lang_special_tokens(self.src_lang						)




			def   lowerCamelCase__  (					self    :       Dict						)   ->			List[Any]:







								"""simple docstring"""
								return self.set_tgt_lang_special_tokens(self.tgt_lang						)




			def   lowerCamelCase__  (					self    :       Tuple							, _snake_case    :       List[str]						)   ->			None:







								"""simple docstring"""
								A_								=    self.convert_tokens_to_ids(_snake_case						)
								A_								=    []
								A_								=    [self.eos_token_id, self.cur_lang_code]

								A_								=    self.convert_ids_to_tokens(self.prefix_tokens						)
								A_								=    self.convert_ids_to_tokens(self.suffix_tokens						)

								A_								=    processors.TemplateProcessing(
								    single=prefix_tokens_str + ["$A"] + suffix_tokens_str							, pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str							, special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str							, self.prefix_tokens + self.suffix_tokens						)						)							, )




			def   lowerCamelCase__  (					self    :       List[str]							, _snake_case    :       str						)   ->			None:







								"""simple docstring"""
								A_								=    self.convert_tokens_to_ids(_snake_case						)
								A_								=    []
								A_								=    [self.eos_token_id, self.cur_lang_code]

								A_								=    self.convert_ids_to_tokens(self.prefix_tokens						)
								A_								=    self.convert_ids_to_tokens(self.suffix_tokens						)

								A_								=    processors.TemplateProcessing(
								    single=prefix_tokens_str + ["$A"] + suffix_tokens_str							, pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str							, special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str							, self.prefix_tokens + self.suffix_tokens						)						)							, )






			def   lowerCamelCase__  (					self    :       Union[str, Any]							, _snake_case    :       str							, _snake_case    :       Optional[str] = None						)   ->			Tuple[str]:







								"""simple docstring"""
								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(_snake_case						):
													logger.error(F'Vocabulary path ({save_directory}) should be a directory.'						)
													return
								A_								=    os.path.join(
								    _snake_case							, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

								if os.path.abspath(self.vocab_file						) != os.path.abspath(_snake_case						):
													copyfile(self.vocab_file							, _snake_case						)

								return (out_vocab_file,)




