


"""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


UpperCAmelCase				=						logging.get_logger(__name__)

UpperCAmelCase				=						"""▁"""

UpperCAmelCase				=						{
    """vocab_file""": """vocab.json""",
    """spm_file""": """sentencepiece.bpe.model""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

UpperCAmelCase				=						{
    """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""",
    },
}

UpperCAmelCase				=						{
    """facebook/m2m100_418M""": 1024,
}

# fmt: off
UpperCAmelCase				=						{
    """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__				(					A_				):
   __UpperCAmelCase							       =					VOCAB_FILES_NAMES
   __UpperCAmelCase							       =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase							       =					PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase							       =					['''input_ids''', '''attention_mask''']

   __UpperCAmelCase							       =					[]
   __UpperCAmelCase							       =					[]





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

      _lowerCamelCase	:					List[Any]   =		language_codes
      _lowerCamelCase	:					List[Any]   =		FAIRSEQ_LANGUAGE_CODES[language_codes]
      _lowerCamelCase	:					str   =		{lang_code: F'__{lang_code}__' for lang_code in fairseq_language_code}

      _lowerCamelCase	:					Optional[Any]   =		kwargs.get("""additional_special_tokens"""      ,   [])
      kwargs["additional_special_tokens"] += [
          self.get_lang_token(SCREAMING_SNAKE_CASE)
          for lang_code in fairseq_language_code
          if self.get_lang_token(SCREAMING_SNAKE_CASE) not in kwargs["additional_special_tokens"]
      ]

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

      _lowerCamelCase	:					Union[str, Any]   =		vocab_file
      _lowerCamelCase	:					str   =		load_json(SCREAMING_SNAKE_CASE)
      _lowerCamelCase	:					List[Any]   =		{v: k for k, v in self.encoder.items()}
      _lowerCamelCase	:					Optional[int]   =		spm_file
      _lowerCamelCase	:					Union[str, Any]   =		load_spm(SCREAMING_SNAKE_CASE      ,   self.sp_model_kwargs)

      _lowerCamelCase	:					Optional[int]   =		len(self.encoder)

      _lowerCamelCase	:					Dict   =		{
          self.get_lang_token(SCREAMING_SNAKE_CASE): self.encoder_size + i for i, lang_code in enumerate(SCREAMING_SNAKE_CASE)
      }
      _lowerCamelCase	:					List[Any]   =		{lang_code: self.encoder_size + i for i, lang_code in enumerate(SCREAMING_SNAKE_CASE)}
      _lowerCamelCase	:					str   =		{v: k for k, v in self.lang_token_to_id.items()}

      _lowerCamelCase	:					List[str]   =		src_lang if src_lang is not None else """en"""
      _lowerCamelCase	:					List[str]   =		tgt_lang
      _lowerCamelCase	:					List[str]   =		self.get_lang_id(self._src_lang)
      self.set_src_lang_special_tokens(self._src_lang)

      _lowerCamelCase	:					Dict   =		num_madeup_words





   @property
   def 		UpperCamelCase_  (							self)  ->  int:
      return len(self.encoder) + len(self.lang_token_to_id)





   @property
   def 		UpperCamelCase_  (							self)  ->  str:
      return self._src_lang





   @src_lang.setter
   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  None:
      _lowerCamelCase	:					Dict   =		new_src_lang
      self.set_src_lang_special_tokens(self._src_lang)





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  List[str]:
      return self.sp_model.encode(SCREAMING_SNAKE_CASE      ,   out_type=SCREAMING_SNAKE_CASE)





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  List[str]:
      if token in self.lang_token_to_id:
         return self.lang_token_to_id[token]
      return self.encoder.get(SCREAMING_SNAKE_CASE      ,   self.encoder[self.unk_token])





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  str:
      if index in self.id_to_lang_token:
         return self.id_to_lang_token[index]
      return self.decoder.get(SCREAMING_SNAKE_CASE      ,   self.unk_token)





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  Dict:
      _lowerCamelCase	:					Tuple   =		[]
      _lowerCamelCase	:					Optional[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(SCREAMING_SNAKE_CASE) + token
            _lowerCamelCase	:					Tuple   =		[]
         else:
            current_sub_tokens.append(SCREAMING_SNAKE_CASE)
      out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE)
      return out_string.strip()





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE = None      ,   SCREAMING_SNAKE_CASE = False)  ->  List[int]:

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

      _lowerCamelCase	:					Union[str, Any]   =		[1] * len(self.prefix_tokens)
      _lowerCamelCase	:					Dict   =		[1] * len(self.suffix_tokens)
      if token_ids_a is None:
         return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE)) + suffix_ones
      return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE)) + ([0] * len(SCREAMING_SNAKE_CASE)) + suffix_ones





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE = None)  ->  List[int]:
      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)  ->  Dict:
      _lowerCamelCase	:					Dict   =		{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE): i for i in range(self.vocab_size)}
      vocab.update(self.added_tokens_encoder)
      return vocab





   def __getstate__(							self)  ->  Dict:
      _lowerCamelCase	:					str   =		self.__dict__.copy()
      _lowerCamelCase	:					List[Any]   =		None
      return state





   def __setstate__(							self      ,   SCREAMING_SNAKE_CASE)  ->  None:
      _lowerCamelCase	:					Any   =		d

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

      _lowerCamelCase	:					Any   =		load_spm(self.spm_file      ,   self.sp_model_kwargs)





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE = None)  ->  Tuple[str]:
      _lowerCamelCase	:					Optional[int]   =		Path(SCREAMING_SNAKE_CASE)
      if not save_dir.is_dir():
         raise OSError(F'{save_directory} should be a directory')
      _lowerCamelCase	:					Any   =		save_dir / (
          (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""vocab_file"""]
      )
      _lowerCamelCase	:					Optional[Any]   =		save_dir / (
          (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""spm_file"""]
      )

      save_json(self.encoder      ,   SCREAMING_SNAKE_CASE)

      if os.path.abspath(self.spm_file) != os.path.abspath(SCREAMING_SNAKE_CASE) and os.path.isfile(self.spm_file):
         copyfile(self.spm_file      ,   SCREAMING_SNAKE_CASE)
      elif not os.path.isfile(self.spm_file):
         with open(SCREAMING_SNAKE_CASE      ,   """wb""") as fi:
            _lowerCamelCase	:					Union[str, Any]   =		self.sp_model.serialized_model_proto()
            fi.write(SCREAMING_SNAKE_CASE)

      return (str(SCREAMING_SNAKE_CASE), str(SCREAMING_SNAKE_CASE))





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE = "en"      ,   SCREAMING_SNAKE_CASE = None      ,   SCREAMING_SNAKE_CASE = "ro"      ,   **SCREAMING_SNAKE_CASE      ,   )  ->  BatchEncoding:
      _lowerCamelCase	:					List[Any]   =		src_lang
      _lowerCamelCase	:					Union[str, Any]   =		tgt_lang
      self.set_src_lang_special_tokens(self.src_lang)
      return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)  ->  List[str]:
      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	:					List[str]   =		src_lang
      _lowerCamelCase	:					str   =		self(SCREAMING_SNAKE_CASE      ,   add_special_tokens=SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)
      _lowerCamelCase	:					List[Any]   =		self.get_lang_id(SCREAMING_SNAKE_CASE)
      _lowerCamelCase	:					str   =		tgt_lang_id
      return inputs





   def 		UpperCamelCase_  (							self)  ->  Any:
      self.set_src_lang_special_tokens(self.src_lang)





   def 		UpperCamelCase_  (							self)  ->  Tuple:
      self.set_tgt_lang_special_tokens(self.tgt_lang)





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  None:
      _lowerCamelCase	:					List[Any]   =		self.get_lang_token(SCREAMING_SNAKE_CASE)
      _lowerCamelCase	:					List[str]   =		self.lang_token_to_id[lang_token]
      _lowerCamelCase	:					str   =		[self.cur_lang_id]
      _lowerCamelCase	:					int   =		[self.eos_token_id]





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  None:
      _lowerCamelCase	:					int   =		self.get_lang_token(SCREAMING_SNAKE_CASE)
      _lowerCamelCase	:					Optional[Any]   =		self.lang_token_to_id[lang_token]
      _lowerCamelCase	:					List[Any]   =		[self.cur_lang_id]
      _lowerCamelCase	:					Tuple   =		[self.eos_token_id]





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  str:
      return self.lang_code_to_token[lang]





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  int:
      _lowerCamelCase	:					int   =		self.get_lang_token(SCREAMING_SNAKE_CASE)
      return self.lang_token_to_id[lang_token]







def 				_snake_case      (   __snake_case							:      str						, __snake_case							:      Dict[str, Any]   ):




   """simple docstring"""







   _lowerCamelCase	:					List[str]   =		sentencepiece.SentencePieceProcessor(**__snake_case   )
   spm.Load(str(__snake_case   )   )
   return spm

def 				_snake_case      (   __snake_case							:      str   ):




   """simple docstring"""







   with open(__snake_case						, """r"""   ) as f:
      return json.load(__snake_case   )





def 				_snake_case      (   __snake_case							:      List[str]						, __snake_case							:      str   ):




   """simple docstring"""







   with open(__snake_case						, """w"""   ) as f:
      json.dump(__snake_case						, __snake_case						, indent=2   )







'''simple docstring'''



def       _UpperCamelCase			(_lowerCamelCase				:  int						)-> int:




     '''simple docstring'''





     __snake_case            =	[[0 for _ in range(_lowerCamelCase						)] for _ in range(m + 1						)]
     for i in range(m + 1						):
          __snake_case            =	1

     for n in range(m + 1						):
          for k in range(1 ,						_lowerCamelCase						):
               memo[n][k] += memo[n][k - 1]
               if n - k > 0:
                    memo[n][k] += memo[n - k - 1][k]

     return memo[m][m - 1]


if __name__ == "__main__":
     import sys

     if len(sys.argv) == 1:
          try:
               UpperCAmelCase_							:	List[str]	     =		int(input('''Enter a number: ''').strip())
               print(partition(n))
          except ValueError:
               print('''Please enter a number.''')
     else:
          try:
               UpperCAmelCase_							:	Union[str, Any]	     =		int(sys.argv[1])
               print(partition(n))
          except ValueError:
               print('''Please pass a number.''')






