



"""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, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


__SCREAMING_SNAKE_CASE  :						Dict    							=      logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE  :						str    							=      '''▁'''

__SCREAMING_SNAKE_CASE  :						str    							=      {'''vocab_file''': '''sentencepiece.bpe.model'''}

__SCREAMING_SNAKE_CASE  :						Optional[int]    							=      {
    '''vocab_file''': {
        '''facebook/mbart-large-50-one-to-many-mmt''': (
            '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model'''
        ),
    }
}

__SCREAMING_SNAKE_CASE  :						str    							=      {
    '''facebook/mbart-large-50-one-to-many-mmt''': 1_0_2_4,
}

# fmt: off
__SCREAMING_SNAKE_CASE  :						Dict    							=      ['''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''', '''af_ZA''', '''az_AZ''', '''bn_IN''', '''fa_IR''', '''he_IL''', '''hr_HR''', '''id_ID''', '''ka_GE''', '''km_KH''', '''mk_MK''', '''ml_IN''', '''mn_MN''', '''mr_IN''', '''pl_PL''', '''ps_AF''', '''pt_XX''', '''sv_SE''', '''sw_KE''', '''ta_IN''', '''te_IN''', '''th_TH''', '''tl_XX''', '''uk_UA''', '''ur_PK''', '''xh_ZA''', '''gl_ES''', '''sl_SI''']


class 							lowerCamelCase_(   A__    ):





					'''simple docstring'''



					lowercase__   :       str										= VOCAB_FILES_NAMES
					lowercase__   :       str										= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase__   :       Optional[int]										= PRETRAINED_VOCAB_FILES_MAP
					lowercase__   :       int										= ['input_ids', 'attention_mask']

					lowercase__   :       List[int]										= []
					lowercase__   :       List[int]										= []

					def __init__(    self				,       lowerCamelCase__				,       lowerCamelCase__=None				,       lowerCamelCase__=None				,       lowerCamelCase__="</s>"				,       lowerCamelCase__="</s>"				,       lowerCamelCase__="<s>"				,       lowerCamelCase__="<unk>"				,       lowerCamelCase__="<pad>"				,       lowerCamelCase__="<mask>"				,       lowerCamelCase__ = None				,       **lowerCamelCase__				,       ):
									# Mask token behave like a normal word, i.e. include the space before it
									_lowerCamelCase        =				AddedToken(lowerCamelCase__				,       lstrip=lowerCamelCase__				,       rstrip=lowerCamelCase__   ) if isinstance(lowerCamelCase__				,       lowerCamelCase__   ) else mask_token

									_lowerCamelCase        =				{} if sp_model_kwargs is None else sp_model_kwargs

									_lowerCamelCase        =				kwargs.get('''additional_special_tokens'''				,       []   )
									kwargs["additional_special_tokens"] += [
									    code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
									]

									super().__init__(
									    src_lang=lowerCamelCase__				,       tgt_lang=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__				,       )

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

									# Original fairseq vocab and spm vocab must be "aligned":
									# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
									# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
									# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
									# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

									# Mimic fairseq token-to-id alignment for the first 4 token
									_lowerCamelCase        =				{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

									# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
									_lowerCamelCase        =				1

									_lowerCamelCase        =				len(self.sp_model   )
									_lowerCamelCase        =				{
									    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowerCamelCase__   )
									}
									_lowerCamelCase        =				{v: k for k, v in self.lang_code_to_id.items()}
									_lowerCamelCase        =				len(self.sp_model   ) + len(self.lang_code_to_id   ) + self.fairseq_offset

									self.fairseq_tokens_to_ids.update(self.lang_code_to_id   )
									_lowerCamelCase        =				{v: k for k, v in self.fairseq_tokens_to_ids.items()}

									_lowerCamelCase        =				src_lang if src_lang is not None else '''en_XX'''
									_lowerCamelCase        =				self.lang_code_to_id[self._src_lang]
									_lowerCamelCase        =				tgt_lang
									self.set_src_lang_special_tokens(self._src_lang   )

					@property
					def 			snake_case__      (    self   ):
									return len(self.sp_model   ) + len(self.lang_code_to_id   ) + self.fairseq_offset + 1  # Plus 1 for the mask token

					@property
					def 			snake_case__      (    self   ):
									return self._src_lang

					@src_lang.setter
					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				new_src_lang
									self.set_src_lang_special_tokens(self._src_lang   )

					def __getstate__(    self   ):
									_lowerCamelCase        =				self.__dict__.copy()
									_lowerCamelCase        =				None
									return state

					def __setstate__(    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				d

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

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

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

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									return self.sp_model.encode(lowerCamelCase__				,       out_type=lowerCamelCase__   )

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
									_lowerCamelCase        =				self.sp_model.PieceToId(lowerCamelCase__   )

									# Need to return unknown token if the SP model returned 0
									return spm_id + self.fairseq_offset if spm_id else self.unk_token_id

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									if index in self.fairseq_ids_to_tokens:
													return self.fairseq_ids_to_tokens[index]
									return self.sp_model.IdToPiece(index - self.fairseq_offset   )

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				[]
									_lowerCamelCase        =				''''''
									_lowerCamelCase        =				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
																	_lowerCamelCase        =				True
																	_lowerCamelCase        =				[]
													else:
																	current_sub_tokens.append(lowerCamelCase__   )
																	_lowerCamelCase        =				False
									out_string += self.sp_model.decode(lowerCamelCase__   )
									return out_string.strip()

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									if not os.path.isdir(lowerCamelCase__   ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""   )
													return
									_lowerCamelCase        =				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:
																	_lowerCamelCase        =				self.sp_model.serialized_model_proto()
																	fi.write(lowerCamelCase__   )

									return (out_vocab_file,)

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None				,       lowerCamelCase__ = False   ):

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

									_lowerCamelCase        =				[1] * len(self.prefix_tokens   )
									_lowerCamelCase        =				[1] * len(self.suffix_tokens   )
									if token_ids_a is None:
													return prefix_ones + ([0] * len(lowerCamelCase__   )) + suffix_ones
									return prefix_ones + ([0] * len(lowerCamelCase__   )) + ([0] * len(lowerCamelCase__   )) + suffix_ones

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									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 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__				,       lowerCamelCase__				,       lowerCamelCase__				,       **lowerCamelCase__   ):
									if src_lang is None or tgt_lang is None:
													raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model'''   )
									_lowerCamelCase        =				src_lang
									_lowerCamelCase        =				self(lowerCamelCase__				,       add_special_tokens=lowerCamelCase__				,       return_tensors=lowerCamelCase__				,       **lowerCamelCase__   )
									_lowerCamelCase        =				self.convert_tokens_to_ids(lowerCamelCase__   )
									_lowerCamelCase        =				tgt_lang_id
									return inputs

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = "en_XX"				,       lowerCamelCase__ = None				,       lowerCamelCase__ = "ro_RO"				,       **lowerCamelCase__				,       ):
									_lowerCamelCase        =				src_lang
									_lowerCamelCase        =				tgt_lang
									return super().prepare_seqaseq_batch(lowerCamelCase__				,       lowerCamelCase__				,       **lowerCamelCase__   )

					def 			snake_case__      (    self   ):
									return self.set_src_lang_special_tokens(self.src_lang   )

					def 			snake_case__      (    self   ):
									return self.set_tgt_lang_special_tokens(self.tgt_lang   )

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				self.lang_code_to_id[src_lang]
									_lowerCamelCase        =				[self.cur_lang_code_id]
									_lowerCamelCase        =				[self.eos_token_id]





					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				self.lang_code_to_id[tgt_lang]
									_lowerCamelCase        =				[self.cur_lang_code_id]
									_lowerCamelCase        =				[self.eos_token_id]





"""simple docstring"""
from __future__ import annotations

from math import pow, sqrt



def        lowerCAmelCase_(   lowercase_     :							float						,   lowercase_     :							float						,   lowercase_     :							float							)	->       dict[str, float]:
				if (resistance, reactance, impedance).count(0							) != 1:
								raise ValueError('''One and only one argument must be 0'''							)
				if resistance == 0:
								return {"resistance": sqrt(pow(lowercase_						,   2							) - pow(lowercase_						,   2							)							)}
				elif reactance == 0:
								return {"reactance": sqrt(pow(lowercase_						,   2							) - pow(lowercase_						,   2							)							)}
				elif impedance == 0:
								return {"impedance": sqrt(pow(lowercase_						,   2							) + pow(lowercase_						,   2							)							)}
				else:
								raise ValueError('''Exactly one argument must be 0'''							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()
