



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


_lowercase     							=						logging.get_logger(__name__)

_lowercase     							=						'''▁'''

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

_lowercase     							=						{
    '''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'''
        ),
    }
}

_lowercase     							=						{
    '''facebook/mbart-large-50-one-to-many-mmt''': 10_24,
}

# fmt: off
_lowercase     							=						['''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 				__A					( A_      ):
			UpperCamelCase					:Dict     =			VOCAB_FILES_NAMES
			UpperCamelCase					:List[Any]     =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase					:List[Any]     =			PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase					:int     =			['''input_ids''', '''attention_mask''']

			UpperCamelCase					:List[str]     =			[]
			UpperCamelCase					:List[Any]     =			[]





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

						lowerCamelCase__ :      str								=		{} if sp_model_kwargs is None else sp_model_kwargs

						lowerCamelCase__ :      List[str]								=		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=__A							,    tgt_lang=__A							,    eos_token=__A							,    unk_token=__A							,    sep_token=__A							,    cls_token=__A							,    pad_token=__A							,    mask_token=__A							,    sp_model_kwargs=self.sp_model_kwargs							,    **__A							,    )

						lowerCamelCase__ :      Union[str, Any]								=		spm.SentencePieceProcessor(**self.sp_model_kwargs				)
						self.sp_model.Load(str(__A				)				)
						lowerCamelCase__ :      Union[str, Any]								=		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__ :      Any								=		{"""<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__ :      int								=		1

						lowerCamelCase__ :      int								=		len(self.sp_model				)
						lowerCamelCase__ :      Dict								=		{
						    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(__A				)
						}
						lowerCamelCase__ :      Optional[int]								=		{v: k for k, v in self.lang_code_to_id.items()}
						lowerCamelCase__ :      Optional[int]								=		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__ :      List[Any]								=		{v: k for k, v in self.fairseq_tokens_to_ids.items()}

						lowerCamelCase__ :      Optional[Any]								=		src_lang if src_lang is not None else """en_XX"""
						lowerCamelCase__ :      Optional[int]								=		self.lang_code_to_id[self._src_lang]
						lowerCamelCase__ :      str								=		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							,    __magic_name__				):
						lowerCamelCase__ :      List[Any]								=		new_src_lang
						self.set_src_lang_special_tokens(self._src_lang				)





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





			def __setstate__(self							,    __magic_name__				):
						lowerCamelCase__ :      Any								=		d

						# for backward compatibility
						if not hasattr(self							,    """sp_model_kwargs"""				):
									lowerCamelCase__ :      Optional[Any]								=		{}

						lowerCamelCase__ :      Dict								=		spm.SentencePieceProcessor(**self.sp_model_kwargs				)
						self.sp_model.Load(self.vocab_file				)





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





			def        _snake_case    (self							,    __magic_name__				):
						return self.sp_model.encode(__A							,    out_type=__A				)





			def        _snake_case    (self							,    __magic_name__				):
						if token in self.fairseq_tokens_to_ids:
									return self.fairseq_tokens_to_ids[token]
						lowerCamelCase__ :      Dict								=		self.sp_model.PieceToId(__A				)

						# 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							,    __magic_name__				):
						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							,    __magic_name__				):
						lowerCamelCase__ :      Tuple								=		[]
						lowerCamelCase__ :      Dict								=		""""""
						lowerCamelCase__ :      List[Any]								=		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(__A				) + token
												lowerCamelCase__ :      int								=		True
												lowerCamelCase__ :      Dict								=		[]
									else:
												current_sub_tokens.append(__A				)
												lowerCamelCase__ :      Optional[Any]								=		False
						out_string += self.sp_model.decode(__A				)
						return out_string.strip()





			def        _snake_case    (self							,    __magic_name__							,    __magic_name__ = None				):
						if not os.path.isdir(__A				):
									logger.error(f"Vocabulary path ({save_directory}) should be a directory"				)
									return
						lowerCamelCase__ :      Tuple								=		os.path.join(
						    __A							,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

						if os.path.abspath(self.vocab_file				) != os.path.abspath(__A				) and os.path.isfile(self.vocab_file				):
									copyfile(self.vocab_file							,    __A				)
						elif not os.path.isfile(self.vocab_file				):
									with open(__A							,    """wb"""				) as fi:
												lowerCamelCase__ :      Optional[int]								=		self.sp_model.serialized_model_proto()
												fi.write(__A				)

						return (out_vocab_file,)





			def        _snake_case    (self							,    __magic_name__							,    __magic_name__ = None							,    __magic_name__ = 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__ :      Optional[Any]								=		[1] * len(self.prefix_tokens				)
						lowerCamelCase__ :      List[Any]								=		[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        _snake_case    (self							,    __magic_name__							,    __magic_name__ = 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							,    __magic_name__							,    __magic_name__							,    __magic_name__							,    __magic_name__							,    **__magic_name__				):
						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__ :      Union[str, Any]								=		src_lang
						lowerCamelCase__ :      Dict								=		self(__A							,    add_special_tokens=__A							,    return_tensors=__A							,    **__A				)
						lowerCamelCase__ :      str								=		self.convert_tokens_to_ids(__A				)
						lowerCamelCase__ :      List[Any]								=		tgt_lang_id
						return inputs





			def        _snake_case    (self							,    __magic_name__							,    __magic_name__ = "en_XX"							,    __magic_name__ = None							,    __magic_name__ = "ro_RO"							,    **__magic_name__							,    ):
						lowerCamelCase__ :      List[Any]								=		src_lang
						lowerCamelCase__ :      Tuple								=		tgt_lang
						return super().prepare_seqaseq_batch(__A							,    __A							,    **__A				)





			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							,    __magic_name__				):
						lowerCamelCase__ :      Any								=		self.lang_code_to_id[src_lang]
						lowerCamelCase__ :      Optional[Any]								=		[self.cur_lang_code_id]
						lowerCamelCase__ :      Tuple								=		[self.eos_token_id]





			def        _snake_case    (self							,    __magic_name__				):
						lowerCamelCase__ :      List[str]								=		self.lang_code_to_id[tgt_lang]
						lowerCamelCase__ :      Union[str, Any]								=		[self.cur_lang_code_id]
						lowerCamelCase__ :      str								=		[self.eos_token_id]








def      _A				(UpperCamelCase		:      int      ,			UpperCamelCase		:      int )  ->int:



			'''simple docstring'''







			while b:
						lowerCamelCase__							,lowerCamelCase__ :      int								=		b, a % b
			return a






def      _A				(UpperCamelCase		:      int      ,			UpperCamelCase		:      int )  ->int:



			'''simple docstring'''







			return a if b == 0 else euclidean_gcd_recursive(UpperCamelCase      ,			a % b )






def      _A				()  ->str:



			'''simple docstring'''







			print(f"euclidean_gcd(3, 5) = {euclidean_gcd(3      ,			5 )}" )
			print(f"euclidean_gcd(5, 3) = {euclidean_gcd(5      ,			3 )}" )
			print(f"euclidean_gcd(1, 3) = {euclidean_gcd(1      ,			3 )}" )
			print(f"euclidean_gcd(3, 6) = {euclidean_gcd(3      ,			6 )}" )
			print(f"euclidean_gcd(6, 3) = {euclidean_gcd(6      ,			3 )}" )

			print(f"euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3      ,			5 )}" )
			print(f"euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5      ,			3 )}" )
			print(f"euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1      ,			3 )}" )
			print(f"euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3      ,			6 )}" )
			print(f"euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6      ,			3 )}" )


if __name__ == "__main__":
				main()



