





__A     =    256
# Modulus to hash a string
__A     =    100_0003





def 					lowerCAmelCase_			(	__a     ,   __a		)					->		bool:







  """simple docstring"""





  lowerCamelCase__:				Tuple        =len(__a		)
  lowerCamelCase__:				Union[str, Any]        =len(__a		)
  if p_len > t_len:
    return False

  lowerCamelCase__:				Tuple        =0
  lowerCamelCase__:				List[Any]        =0
  lowerCamelCase__:				int        =1

  # Calculating the hash of pattern and substring of text
  for i in range(__a		):
    lowerCamelCase__:				Any        =(ord(pattern[i]		) + p_hash * alphabet_size) % modulus
    lowerCamelCase__:				Optional[Any]        =(ord(text[i]		) + text_hash * alphabet_size) % modulus
    if i == p_len - 1:
      continue
    lowerCamelCase__:				Tuple        =(modulus_power * alphabet_size) % modulus

  for i in range(0     ,   t_len - p_len + 1		):
    if text_hash == p_hash and text[i : i + p_len] == pattern:
      return True
    if i == t_len - p_len:
      continue
    # Calculate the https://en.wikipedia.org/wiki/Rolling_hash
    lowerCamelCase__:				List[Any]        =(
        (text_hash - ord(text[i]		) * modulus_power) * alphabet_size
        + ord(text[i + p_len]		)
    ) % modulus
  return False





def 					lowerCAmelCase_			(	)					->		None:







  """simple docstring"""





  lowerCamelCase__:				Optional[Any]        ="abc1abc12"
  lowerCamelCase__:				Optional[int]        ="alskfjaldsabc1abc1abc12k23adsfabcabc"
  lowerCamelCase__:				Union[str, Any]        ="alskfjaldsk23adsfabcabc"
  assert rabin_karp(__a     ,   __a		) and not rabin_karp(__a     ,   __a		)

  # Test 2)
  lowerCamelCase__:				Optional[Any]        ="ABABX"
  lowerCamelCase__:				str        ="ABABZABABYABABX"
  assert rabin_karp(__a     ,   __a		)

  # Test 3)
  lowerCamelCase__:				Optional[Any]        ="AAAB"
  lowerCamelCase__:				List[Any]        ="ABAAAAAB"
  assert rabin_karp(__a     ,   __a		)

  # Test 4)
  lowerCamelCase__:				str        ="abcdabcy"
  lowerCamelCase__:				Tuple        ="abcxabcdabxabcdabcdabcy"
  assert rabin_karp(__a     ,   __a		)

  # Test 5)
  lowerCamelCase__:				Union[str, Any]        ="Lü"
  lowerCamelCase__:				List[Any]        ="Lüsai"
  assert rabin_karp(__a     ,   __a		)
  lowerCamelCase__:				Optional[Any]        ="Lue"
  assert not rabin_karp(__a     ,   __a		)
  print("Success."		)


if __name__ == "__main__":
     test_rabin_karp()








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     =    logging.get_logger(__name__)

__A     =    "▁"

__A     =    {"vocab_file": "sentencepiece.bpe.model"}

__A     =    {
    "vocab_file": {
        "facebook/nllb-200-distilled-600M": (
            "https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model"
        ),
    }
}

__A     =    {
    "facebook/nllb-200-distilled-600M": 1024,
}

# fmt: off
__A     =    ["ace_Arab", "ace_Latn", "acm_Arab", "acq_Arab", "aeb_Arab", "afr_Latn", "ajp_Arab", "aka_Latn", "amh_Ethi", "apc_Arab", "arb_Arab", "ars_Arab", "ary_Arab", "arz_Arab", "asm_Beng", "ast_Latn", "awa_Deva", "ayr_Latn", "azb_Arab", "azj_Latn", "bak_Cyrl", "bam_Latn", "ban_Latn", "bel_Cyrl", "bem_Latn", "ben_Beng", "bho_Deva", "bjn_Arab", "bjn_Latn", "bod_Tibt", "bos_Latn", "bug_Latn", "bul_Cyrl", "cat_Latn", "ceb_Latn", "ces_Latn", "cjk_Latn", "ckb_Arab", "crh_Latn", "cym_Latn", "dan_Latn", "deu_Latn", "dik_Latn", "dyu_Latn", "dzo_Tibt", "ell_Grek", "eng_Latn", "epo_Latn", "est_Latn", "eus_Latn", "ewe_Latn", "fao_Latn", "pes_Arab", "fij_Latn", "fin_Latn", "fon_Latn", "fra_Latn", "fur_Latn", "fuv_Latn", "gla_Latn", "gle_Latn", "glg_Latn", "grn_Latn", "guj_Gujr", "hat_Latn", "hau_Latn", "heb_Hebr", "hin_Deva", "hne_Deva", "hrv_Latn", "hun_Latn", "hye_Armn", "ibo_Latn", "ilo_Latn", "ind_Latn", "isl_Latn", "ita_Latn", "jav_Latn", "jpn_Jpan", "kab_Latn", "kac_Latn", "kam_Latn", "kan_Knda", "kas_Arab", "kas_Deva", "kat_Geor", "knc_Arab", "knc_Latn", "kaz_Cyrl", "kbp_Latn", "kea_Latn", "khm_Khmr", "kik_Latn", "kin_Latn", "kir_Cyrl", "kmb_Latn", "kon_Latn", "kor_Hang", "kmr_Latn", "lao_Laoo", "lvs_Latn", "lij_Latn", "lim_Latn", "lin_Latn", "lit_Latn", "lmo_Latn", "ltg_Latn", "ltz_Latn", "lua_Latn", "lug_Latn", "luo_Latn", "lus_Latn", "mag_Deva", "mai_Deva", "mal_Mlym", "mar_Deva", "min_Latn", "mkd_Cyrl", "plt_Latn", "mlt_Latn", "mni_Beng", "khk_Cyrl", "mos_Latn", "mri_Latn", "zsm_Latn", "mya_Mymr", "nld_Latn", "nno_Latn", "nob_Latn", "npi_Deva", "nso_Latn", "nus_Latn", "nya_Latn", "oci_Latn", "gaz_Latn", "ory_Orya", "pag_Latn", "pan_Guru", "pap_Latn", "pol_Latn", "por_Latn", "prs_Arab", "pbt_Arab", "quy_Latn", "ron_Latn", "run_Latn", "rus_Cyrl", "sag_Latn", "san_Deva", "sat_Beng", "scn_Latn", "shn_Mymr", "sin_Sinh", "slk_Latn", "slv_Latn", "smo_Latn", "sna_Latn", "snd_Arab", "som_Latn", "sot_Latn", "spa_Latn", "als_Latn", "srd_Latn", "srp_Cyrl", "ssw_Latn", "sun_Latn", "swe_Latn", "swh_Latn", "szl_Latn", "tam_Taml", "tat_Cyrl", "tel_Telu", "tgk_Cyrl", "tgl_Latn", "tha_Thai", "tir_Ethi", "taq_Latn", "taq_Tfng", "tpi_Latn", "tsn_Latn", "tso_Latn", "tuk_Latn", "tum_Latn", "tur_Latn", "twi_Latn", "tzm_Tfng", "uig_Arab", "ukr_Cyrl", "umb_Latn", "urd_Arab", "uzn_Latn", "vec_Latn", "vie_Latn", "war_Latn", "wol_Latn", "xho_Latn", "ydd_Hebr", "yor_Latn", "yue_Hant", "zho_Hans", "zho_Hant", "zul_Latn"]



class        _SCREAMING_SNAKE_CASE						(     __SCREAMING_SNAKE_CASE   ):







 '''simple docstring'''
 lowercase_		=      VOCAB_FILES_NAMES
 lowercase_		=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_		=      PRETRAINED_VOCAB_FILES_MAP
 lowercase_		=      ["input_ids", "attention_mask"]

 lowercase_		=      []
 lowercase_		=      []

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



   '''simple docstring'''



   lowerCamelCase__:				Any        =AddedToken(UpperCAmelCase_	,			lstrip=UpperCAmelCase_	,			rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_	,			UpperCAmelCase_) else mask_token

   lowerCamelCase__:				Any        ={} if sp_model_kwargs is None else sp_model_kwargs
   lowerCamelCase__:				List[str]        =legacy_behaviour

   super().__init__(
       bos_token=UpperCAmelCase_	,			eos_token=UpperCAmelCase_	,			unk_token=UpperCAmelCase_	,			sep_token=UpperCAmelCase_	,			cls_token=UpperCAmelCase_	,			pad_token=UpperCAmelCase_	,			mask_token=UpperCAmelCase_	,			tokenizer_file=UpperCAmelCase_	,			src_lang=UpperCAmelCase_	,			tgt_lang=UpperCAmelCase_	,			additional_special_tokens=UpperCAmelCase_	,			sp_model_kwargs=self.sp_model_kwargs	,			legacy_behaviour=UpperCAmelCase_	,			**UpperCAmelCase_	,			)

   lowerCamelCase__:				Optional[Any]        =spm.SentencePieceProcessor(**self.sp_model_kwargs)
   self.sp_model.Load(str(UpperCAmelCase_))
   lowerCamelCase__:				str        =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>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
   # spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

   # Mimic fairseq token-to-id alignment for the first 4 token
   lowerCamelCase__:				str        ={"<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__:				List[str]        =1

   lowerCamelCase__:				Any        =len(self.sp_model)
   lowerCamelCase__:				Any        ={
       code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(UpperCAmelCase_)
   }
   lowerCamelCase__:				Dict        ={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[str]        ={v: k for k, v in self.fairseq_tokens_to_ids.items()}
   lowerCamelCase__:				List[str]        =list(self.lang_code_to_id.keys())

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

   lowerCamelCase__:				int        =src_lang if src_lang is not None else "eng_Latn"
   lowerCamelCase__:				List[str]        =self.lang_code_to_id[self._src_lang]
   lowerCamelCase__:				Optional[int]        =tgt_lang
   self.set_src_lang_special_tokens(self._src_lang)

 def __getstate__(self    :       List[str])	->int:



   '''simple docstring'''



   lowerCamelCase__:				Optional[int]        =self.__dict__.copy()
   lowerCamelCase__:				Any        =None
   lowerCamelCase__:				Optional[int]        =self.sp_model.serialized_model_proto()
   return state

 def __setstate__(self    :       Dict	,			UpperCAmelCase_    :       Union[str, Any])	->Optional[int]:



   '''simple docstring'''



   lowerCamelCase__:				Dict        =d

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

   lowerCamelCase__:				Dict        =spm.SentencePieceProcessor(**self.sp_model_kwargs)
   self.sp_model.LoadFromSerializedProto(self.sp_model_proto)

 @property
 def 							SCREAMING_SNAKE_CASE_ (self    :       int)	->List[str]:



   '''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 							SCREAMING_SNAKE_CASE_ (self    :       Dict)	->str:



   '''simple docstring'''



   return self._src_lang

 @src_lang.setter
 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int]	,			UpperCAmelCase_    :       str)	->None:



   '''simple docstring'''



   lowerCamelCase__:				Any        =new_src_lang
   self.set_src_lang_special_tokens(self._src_lang)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any]	,			UpperCAmelCase_    :       List[int]	,			UpperCAmelCase_    :       Optional[List[int]] = None	,			UpperCAmelCase_    :       bool = False)	->List[int]:



   '''simple docstring'''



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

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

 def 							SCREAMING_SNAKE_CASE_ (self    :       List[Any]	,			UpperCAmelCase_    :       List[int]	,			UpperCAmelCase_    :       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 							SCREAMING_SNAKE_CASE_ (self    :       Union[str, Any]	,			UpperCAmelCase_    :       List[int]	,			UpperCAmelCase_    :       Optional[List[int]] = None)	->List[int]:



   '''simple docstring'''



   lowerCamelCase__:				Any        =[self.sep_token_id]
   lowerCamelCase__:				List[str]        =[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 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any]	,			UpperCAmelCase_    :       List[Any]	,			UpperCAmelCase_    :       str	,			UpperCAmelCase_    :       Optional[str]	,			UpperCAmelCase_    :       Optional[str]	,			**UpperCAmelCase_    :       Optional[int])	->Dict:



   '''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__:				Optional[int]        =src_lang
   lowerCamelCase__:				Dict        =self(UpperCAmelCase_	,			add_special_tokens=UpperCAmelCase_	,			return_tensors=UpperCAmelCase_	,			**UpperCAmelCase_)
   lowerCamelCase__:				int        =self.convert_tokens_to_ids(UpperCAmelCase_)
   lowerCamelCase__:				Tuple        =tgt_lang_id
   return inputs

 def 							SCREAMING_SNAKE_CASE_ (self    :       Union[str, Any])	->Union[str, Any]:



   '''simple docstring'''



   lowerCamelCase__:				Optional[int]        ={self.convert_ids_to_tokens(UpperCAmelCase_): i for i in range(self.vocab_size)}
   vocab.update(self.added_tokens_encoder)
   return vocab

 def 							SCREAMING_SNAKE_CASE_ (self    :       List[Any]	,			UpperCAmelCase_    :       str)	->List[str]:



   '''simple docstring'''



   return self.sp_model.encode(UpperCAmelCase_	,			out_type=UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_ (self    :       int	,			UpperCAmelCase_    :       Union[str, Any])	->Union[str, Any]:



   '''simple docstring'''



   if token in self.fairseq_tokens_to_ids:
     return self.fairseq_tokens_to_ids[token]
   lowerCamelCase__:				Dict        =self.sp_model.PieceToId(UpperCAmelCase_)

   # 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 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any]	,			UpperCAmelCase_    :       Optional[int])	->List[Any]:



   '''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 							SCREAMING_SNAKE_CASE_ (self    :       Tuple	,			UpperCAmelCase_    :       List[Any])	->int:



   '''simple docstring'''



   lowerCamelCase__:				List[Any]        ="".join(UpperCAmelCase_).replace(UpperCAmelCase_	,			" ").strip()
   return out_string

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



   '''simple docstring'''



   if not os.path.isdir(UpperCAmelCase_):
     logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
     return
   lowerCamelCase__:				str        =os.path.join(
       UpperCAmelCase_	,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])

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

   return (out_vocab_file,)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Tuple	,			UpperCAmelCase_    :       List[str]	,			UpperCAmelCase_    :       str = "eng_Latn"	,			UpperCAmelCase_    :       Optional[List[str]] = None	,			UpperCAmelCase_    :       str = "fra_Latn"	,			**UpperCAmelCase_    :       Dict	,			)	->BatchEncoding:



   '''simple docstring'''



   lowerCamelCase__:				Tuple        =src_lang
   lowerCamelCase__:				Union[str, Any]        =tgt_lang
   return super().prepare_seqaseq_batch(UpperCAmelCase_	,			UpperCAmelCase_	,			**UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int])	->Optional[Any]:



   '''simple docstring'''



   return self.set_src_lang_special_tokens(self.src_lang)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any])	->int:



   '''simple docstring'''



   return self.set_tgt_lang_special_tokens(self.tgt_lang)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int]	,			UpperCAmelCase_    :       List[Any])	->None:



   '''simple docstring'''



   lowerCamelCase__:				int        =self.lang_code_to_id[src_lang]
   if self.legacy_behaviour:
     lowerCamelCase__:				Any        =[]
     lowerCamelCase__:				Tuple        =[self.eos_token_id, self.cur_lang_code]
   else:
     lowerCamelCase__:				Any        =[self.cur_lang_code]
     lowerCamelCase__:				Dict        =[self.eos_token_id]







 def 							SCREAMING_SNAKE_CASE_ (self    :       Dict	,			UpperCAmelCase_    :       str)	->None:



   '''simple docstring'''



   lowerCamelCase__:				Any        =self.lang_code_to_id[lang]
   if self.legacy_behaviour:
     lowerCamelCase__:				int        =[]
     lowerCamelCase__:				str        =[self.eos_token_id, self.cur_lang_code]
   else:
     lowerCamelCase__:				Union[str, Any]        =[self.cur_lang_code]
     lowerCamelCase__:				Optional[Any]        =[self.eos_token_id]

