
'''simple docstring'''


import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

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


__lowercase							:   List[Any]					=     logging.get_logger(__name__)

__lowercase							:   Tuple					=     '''▁'''

__lowercase							:   Optional[Any]					=     {
    '''vocab_file''': '''vocab.json''',
    '''spm_file''': '''sentencepiece.bpe.model''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

__lowercase							:   int					=     {
    '''vocab_file''': {
        '''facebook/m2m100_418M''': '''https://huggingface.co/facebook/m2m100_418M/resolve/main/vocab.json''',
        '''facebook/m2m100_1.2B''': '''https://huggingface.co/facebook/m2m100_1.2B/resolve/main/vocab.json''',
    },
    '''spm_file''': {
        '''facebook/m2m100_418M''': '''https://huggingface.co/facebook/m2m100_418M/resolve/main/sentencepiece.bpe.model''',
        '''facebook/m2m100_1.2B''': '''https://huggingface.co/facebook/m2m100_1.2B/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_config_file''': {
        '''facebook/m2m100_418M''': '''https://huggingface.co/facebook/m2m100_418M/resolve/main/tokenizer_config.json''',
        '''facebook/m2m100_1.2B''': '''https://huggingface.co/facebook/m2m100_1.2B/resolve/main/tokenizer_config.json''',
    },
}

__lowercase							:   Optional[int]					=     {
    '''facebook/m2m100_418M''': 1024,
}

# fmt: off
__lowercase							:   str					=     {
    '''m2m100''': ['''af''', '''am''', '''ar''', '''ast''', '''az''', '''ba''', '''be''', '''bg''', '''bn''', '''br''', '''bs''', '''ca''', '''ceb''', '''cs''', '''cy''', '''da''', '''de''', '''el''', '''en''', '''es''', '''et''', '''fa''', '''ff''', '''fi''', '''fr''', '''fy''', '''ga''', '''gd''', '''gl''', '''gu''', '''ha''', '''he''', '''hi''', '''hr''', '''ht''', '''hu''', '''hy''', '''id''', '''ig''', '''ilo''', '''is''', '''it''', '''ja''', '''jv''', '''ka''', '''kk''', '''km''', '''kn''', '''ko''', '''lb''', '''lg''', '''ln''', '''lo''', '''lt''', '''lv''', '''mg''', '''mk''', '''ml''', '''mn''', '''mr''', '''ms''', '''my''', '''ne''', '''nl''', '''no''', '''ns''', '''oc''', '''or''', '''pa''', '''pl''', '''ps''', '''pt''', '''ro''', '''ru''', '''sd''', '''si''', '''sk''', '''sl''', '''so''', '''sq''', '''sr''', '''ss''', '''su''', '''sv''', '''sw''', '''ta''', '''th''', '''tl''', '''tn''', '''tr''', '''uk''', '''ur''', '''uz''', '''vi''', '''wo''', '''xh''', '''yi''', '''yo''', '''zh''', '''zu'''],
    '''wmt21''': ['''en''', '''ha''', '''is''', '''ja''', '''cs''', '''ru''', '''zh''', '''de''']
}

class 	__lowercase				(  _lowercase    ):
			lowerCamelCase			:		Dict	      =			VOCAB_FILES_NAMES
			lowerCamelCase			:		Optional[int]	      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase			:		str	      =			PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase			:		Optional[Any]	      =			["input_ids", "attention_mask"]

			lowerCamelCase			:		List[int]	      =			[]
			lowerCamelCase			:		List[int]	      =			[]

			def __init__(self			,   A			,   A			,   A=None			,   A=None			,   A="<s>"			,   A="</s>"			,   A="</s>"			,   A="<pad>"			,   A="<unk>"			,   A="m2m100"			,   A = None			,   A=8			,   **A			,   ):
								lowerCamelCase_					:      List[Any]     =		{} if sp_model_kwargs is None else sp_model_kwargs

								lowerCamelCase_					:      List[Any]     =		language_codes
								lowerCamelCase_					:      Optional[int]     =		FAIRSEQ_LANGUAGE_CODES[language_codes]
								lowerCamelCase_					:      Tuple     =		{lang_code: F"""__{lang_code}__""" for lang_code in fairseq_language_code}

								lowerCamelCase_					:      Union[str, Any]     =		kwargs.get('''additional_special_tokens'''			,   []      )
								kwargs["additional_special_tokens"] += [
								    self.get_lang_token(A      )
								    for lang_code in fairseq_language_code
								    if self.get_lang_token(A      ) not in kwargs["additional_special_tokens"]
								]

								super().__init__(
								    src_lang=A			,   tgt_lang=A			,   bos_token=A			,   eos_token=A			,   sep_token=A			,   unk_token=A			,   pad_token=A			,   language_codes=A			,   sp_model_kwargs=self.sp_model_kwargs			,   num_madeup_words=A			,   **A			,   )

								lowerCamelCase_					:      Union[str, Any]     =		vocab_file
								lowerCamelCase_					:      Optional[int]     =		load_json(A      )
								lowerCamelCase_					:      Tuple     =		{v: k for k, v in self.encoder.items()}
								lowerCamelCase_					:      int     =		spm_file
								lowerCamelCase_					:      Dict     =		load_spm(A			,   self.sp_model_kwargs      )

								lowerCamelCase_					:      List[Any]     =		len(self.encoder      )

								lowerCamelCase_					:      Tuple     =		{
								    self.get_lang_token(A      ): self.encoder_size + i for i, lang_code in enumerate(A      )
								}
								lowerCamelCase_					:      int     =		{lang_code: self.encoder_size + i for i, lang_code in enumerate(A      )}
								lowerCamelCase_					:      List[Any]     =		{v: k for k, v in self.lang_token_to_id.items()}

								lowerCamelCase_					:      str     =		src_lang if src_lang is not None else '''en'''
								lowerCamelCase_					:      Dict     =		tgt_lang
								lowerCamelCase_					:      int     =		self.get_lang_id(self._src_lang      )
								self.set_src_lang_special_tokens(self._src_lang      )

								lowerCamelCase_					:      Optional[Any]     =		num_madeup_words

			@property
			def        UpperCAmelCase__ (self      ):
								return len(self.encoder      ) + len(self.lang_token_to_id      )

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

			@src_lang.setter
			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      Tuple     =		new_src_lang
								self.set_src_lang_special_tokens(self._src_lang      )

			def        UpperCAmelCase__ (self			,   A      ):
								return self.sp_model.encode(A			,   out_type=A      )

			def        UpperCAmelCase__ (self			,   A      ):
								if token in self.lang_token_to_id:
													return self.lang_token_to_id[token]
								return self.encoder.get(A			,   self.encoder[self.unk_token]      )

			def        UpperCAmelCase__ (self			,   A      ):
								if index in self.id_to_lang_token:
													return self.id_to_lang_token[index]
								return self.decoder.get(A			,   self.unk_token      )

			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      List[str]     =		[]
								lowerCamelCase_					:      int     =		''''''
								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(A      ) + token
																		lowerCamelCase_					:      Optional[int]     =		[]
													else:
																		current_sub_tokens.append(A      )
								out_string += self.sp_model.decode(A      )
								return out_string.strip()

			def        UpperCAmelCase__ (self			,   A			,   A = None			,   A = False      ):

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

								lowerCamelCase_					:      Any     =		[1] * len(self.prefix_tokens      )
								lowerCamelCase_					:      List[str]     =		[1] * len(self.suffix_tokens      )
								if token_ids_a is None:
													return prefix_ones + ([0] * len(A      )) + suffix_ones
								return prefix_ones + ([0] * len(A      )) + ([0] * len(A      )) + suffix_ones

			def        UpperCAmelCase__ (self			,   A			,   A = 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        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      List[Any]     =		{self.convert_ids_to_tokens(A      ): i for i in range(self.vocab_size      )}
								vocab.update(self.added_tokens_encoder      )
								return vocab

			def __getstate__(self      ):
								lowerCamelCase_					:      Optional[Any]     =		self.__dict__.copy()
								lowerCamelCase_					:      Union[str, Any]     =		None
								return state

			def __setstate__(self			,   A      ):
								lowerCamelCase_					:      Optional[int]     =		d

								# for backward compatibility
								if not hasattr(self			,   '''sp_model_kwargs'''      ):
													lowerCamelCase_					:      Union[str, Any]     =		{}

								lowerCamelCase_					:      Tuple     =		load_spm(self.spm_file			,   self.sp_model_kwargs      )

			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								lowerCamelCase_					:      Optional[Any]     =		Path(A      )
								if not save_dir.is_dir():
													raise OSError(F"""{save_directory} should be a directory"""      )
								lowerCamelCase_					:      Optional[int]     =		save_dir / (
								    (filename_prefix + '''-''' if filename_prefix else '''''') + self.vocab_files_names['''vocab_file''']
								)
								lowerCamelCase_					:      List[Any]     =		save_dir / (
								    (filename_prefix + '''-''' if filename_prefix else '''''') + self.vocab_files_names['''spm_file''']
								)

								save_json(self.encoder			,   A      )

								if os.path.abspath(self.spm_file      ) != os.path.abspath(A      ) and os.path.isfile(self.spm_file      ):
													copyfile(self.spm_file			,   A      )
								elif not os.path.isfile(self.spm_file      ):
													with open(A			,   '''wb'''      ) as fi:
																		lowerCamelCase_					:      Dict     =		self.sp_model.serialized_model_proto()
																		fi.write(A      )

								return (str(A      ), str(A      ))

			def        UpperCAmelCase__ (self			,   A			,   A = "en"			,   A = None			,   A = "ro"			,   **A			,   ):
								lowerCamelCase_					:      str     =		src_lang
								lowerCamelCase_					:      Tuple     =		tgt_lang
								self.set_src_lang_special_tokens(self.src_lang      )
								return super().prepare_seqaseq_batch(A			,   A			,   **A      )

			def        UpperCAmelCase__ (self			,   A			,   A			,   A			,   **A      ):
								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_					:      Dict     =		src_lang
								lowerCamelCase_					:      Tuple     =		self(A			,   add_special_tokens=A			,   **A      )
								lowerCamelCase_					:      str     =		self.get_lang_id(A      )
								lowerCamelCase_					:      str     =		tgt_lang_id
								return inputs

			def        UpperCAmelCase__ (self      ):
								self.set_src_lang_special_tokens(self.src_lang      )

			def        UpperCAmelCase__ (self      ):
								self.set_tgt_lang_special_tokens(self.tgt_lang      )

			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      Any     =		self.get_lang_token(A      )
								lowerCamelCase_					:      int     =		self.lang_token_to_id[lang_token]
								lowerCamelCase_					:      str     =		[self.cur_lang_id]
								lowerCamelCase_					:      str     =		[self.eos_token_id]

			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      Tuple     =		self.get_lang_token(A      )
								lowerCamelCase_					:      Optional[Any]     =		self.lang_token_to_id[lang_token]
								lowerCamelCase_					:      List[Any]     =		[self.cur_lang_id]
								lowerCamelCase_					:      Any     =		[self.eos_token_id]

			def        UpperCAmelCase__ (self			,   A      ):
								return self.lang_code_to_token[lang]






			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      str     =		self.get_lang_token(A      )
								return self.lang_token_to_id[lang_token]




def lowercase_	(   _lowercase			,       _lowercase				)     ->							sentencepiece.SentencePieceProcessor:
					'''simple docstring'''

					lowerCamelCase_					:      Dict     =		sentencepiece.SentencePieceProcessor(**_lowercase				)
					spm.Load(str(_lowercase				)				)
					return spm




def lowercase_	(   _lowercase				)     ->							Union[Dict, List]:
					'''simple docstring'''

					with open(_lowercase			,       '''r'''				) as f:
										return json.load(_lowercase				)






def lowercase_	(   _lowercase			,       _lowercase				)     ->							None:
					'''simple docstring'''

					with open(_lowercase			,       '''w'''				) as f:
										json.dump(_lowercase			,       _lowercase			,       indent=2				)




'''simple docstring'''


from __future__ import annotations




def lowercase_	(   _lowercase			,       _lowercase			,       _lowercase				)     ->							dict[str, float]:
					'''simple docstring'''

					if (voltage, current, resistance).count(0				) != 1:
										raise ValueError('''One and only one argument must be 0'''				)
					if resistance < 0:
										raise ValueError('''Resistance cannot be negative'''				)
					if voltage == 0:
										return {"voltage": float(current * resistance				)}
					elif current == 0:
										return {"current": voltage / resistance}
					elif resistance == 0:
										return {"resistance": voltage / current}
					else:
										raise ValueError('''Exactly one argument must be 0'''				)


if __name__ == "__main__":
					import doctest

					doctest.testmod()


