






'''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


a_						:       List[str]      			=				logging.get_logger(__name__)

a_						:       Any      			=				"""▁"""

a_						:       Dict      			=				{"""vocab_file""": """sentencepiece.bpe.model"""}

a_						:       Any      			=				{
    """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"""
        ),
    }
}

a_						:       str      			=				{
    """facebook/mbart-large-50-one-to-many-mmt""": 1024,
}

# fmt: off
a_						:       Optional[Any]      			=				["""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   snake_case					(					_UpperCAmelCase    ):





  """simple docstring"""




  _lowerCamelCase						=						VOCAB_FILES_NAMES
  _lowerCamelCase						=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _lowerCamelCase						=						PRETRAINED_VOCAB_FILES_MAP
  _lowerCamelCase						=						["""input_ids""", """attention_mask"""]

  _lowerCamelCase						=						[]
  _lowerCamelCase						=						[]






  def __init__(					self    ,						UpperCamelCase    ,						UpperCamelCase=None    ,						UpperCamelCase=None    ,						UpperCamelCase="</s>"    ,						UpperCamelCase="</s>"    ,						UpperCamelCase="<s>"    ,						UpperCamelCase="<unk>"    ,						UpperCamelCase="<pad>"    ,						UpperCamelCase="<mask>"    ,						UpperCamelCase = None    ,						**UpperCamelCase    ,						):







   """simple docstring"""
   # Mask token behave like a normal word, i.e. include the space before it
   lowerCamelCase_  				=						AddedToken(lowercase__    ,						lstrip=lowercase__    ,						rstrip=lowercase__  ) if isinstance(lowercase__    ,						lowercase__  ) 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=lowercase__    ,						tgt_lang=lowercase__    ,						eos_token=lowercase__    ,						unk_token=lowercase__    ,						sep_token=lowercase__    ,						cls_token=lowercase__    ,						pad_token=lowercase__    ,						mask_token=lowercase__    ,						sp_model_kwargs=self.sp_model_kwargs    ,						**lowercase__    ,						)

   lowerCamelCase_  				=						spm.SentencePieceProcessor(**self.sp_model_kwargs  )
   self.sp_model.Load(str(lowercase__  )  )
   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(lowercase__  )
   }
   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  ):







   """simple docstring"""
   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  ):







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






  @src_lang.setter
  def 						snake_case	(					self    ,						UpperCamelCase  ):







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






  def __getstate__(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.__dict__.copy()
   lowerCamelCase_  				=						None
   return state






  def __setstate__(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   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  ):







   """simple docstring"""
   lowerCamelCase_  				=						{self.convert_ids_to_tokens(lowercase__  ): i for i in range(self.vocab_size  )}
   vocab.update(self.added_tokens_encoder  )
   return vocab






  def 						snake_case	(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   return self.sp_model.encode(lowercase__    ,						out_type=lowercase__  )






  def 						snake_case	(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   if token in self.fairseq_tokens_to_ids:
    return self.fairseq_tokens_to_ids[token]
   lowerCamelCase_  				=						self.sp_model.PieceToId(lowercase__  )

   # 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    ,						UpperCamelCase  ):







   """simple docstring"""
   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    ,						UpperCamelCase  ):







   """simple docstring"""
   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(lowercase__  ) + token
     lowerCamelCase_  				=						True
     lowerCamelCase_  				=						[]
    else:
     current_sub_tokens.append(lowercase__  )
     lowerCamelCase_  				=						False
   out_string += self.sp_model.decode(lowercase__  )
   return out_string.strip()






  def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase = None  ):







   """simple docstring"""
   if not os.path.isdir(lowercase__  ):
    logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
    return
   lowerCamelCase_  				=						os.path.join(
       lowercase__    ,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]  )

   if os.path.abspath(self.vocab_file  ) != os.path.abspath(lowercase__  ) and os.path.isfile(self.vocab_file  ):
    copyfile(self.vocab_file    ,						lowercase__  )
   elif not os.path.isfile(self.vocab_file  ):
    with open(lowercase__    ,						"wb"  ) as fi:
     lowerCamelCase_  				=						self.sp_model.serialized_model_proto()
     fi.write(lowercase__  )

   return (out_vocab_file,)






  def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase = None    ,						UpperCamelCase = False  ):







   """simple docstring"""

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

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






  def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase = None  ):







   """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 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase    ,						UpperCamelCase    ,						UpperCamelCase    ,						**UpperCamelCase  ):







   """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"  )
   lowerCamelCase_  				=						src_lang
   lowerCamelCase_  				=						self(lowercase__    ,						add_special_tokens=lowercase__    ,						return_tensors=lowercase__    ,						**lowercase__  )
   lowerCamelCase_  				=						self.convert_tokens_to_ids(lowercase__  )
   lowerCamelCase_  				=						tgt_lang_id
   return inputs






  def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase = "en_XX"    ,						UpperCamelCase = None    ,						UpperCamelCase = "ro_RO"    ,						**UpperCamelCase    ,						):







   """simple docstring"""
   lowerCamelCase_  				=						src_lang
   lowerCamelCase_  				=						tgt_lang
   return super().prepare_seqaseq_batch(lowercase__    ,						lowercase__    ,						**lowercase__  )






  def 						snake_case	(					self  ):







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






  def 						snake_case	(					self  ):







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






  def 						snake_case	(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.lang_code_to_id[src_lang]
   lowerCamelCase_  				=						[self.cur_lang_code_id]
   lowerCamelCase_  				=						[self.eos_token_id]







  def 						snake_case	(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.lang_code_to_id[tgt_lang]
   lowerCamelCase_  				=						[self.cur_lang_code_id]
   lowerCamelCase_  				=						[self.eos_token_id]







'''simple docstring'''

def __snake_case      (   UpperCAmelCase_		:		int      ,       UpperCAmelCase_		:		int	):
 return "\n".join(
     F'''{number} * {i} = {number * i}''' for i in range(1      ,       number_of_terms + 1	)	)


if __name__ == "__main__":
     print(multiplication_table(number=5, number_of_terms=10))



