

"""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[Any]           =			logging.get_logger(__name__)

A_				:      Tuple           =			'▁'

A_				:      Dict           =			{'vocab_file': 'sentencepiece.bpe.model'}

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

A_				:      Dict           =			{
    'facebook/nllb-200-distilled-600M': 1_024,
}

# fmt: off
A_				:      Union[str, Any]           =			['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  lowerCamelCase    (SCREAMING_SNAKE_CASE__      ):
			lowerCamelCase__ :		Union[str, Any]       		=				VOCAB_FILES_NAMES
			lowerCamelCase__ :		Optional[int]       		=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase__ :		Union[str, Any]       		=				PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase__ :		Optional[Any]       		=				['input_ids', 'attention_mask']

			lowerCamelCase__ :		List[Any]       		=				[]
			lowerCamelCase__ :		Tuple       		=				[]

			def __init__(       self					:    Dict     ,					__UpperCAmelCase					:    Union[str, Any]     ,					__UpperCAmelCase					:    Dict="<s>"     ,					__UpperCAmelCase					:    Optional[Any]="</s>"     ,					__UpperCAmelCase					:    List[str]="</s>"     ,					__UpperCAmelCase					:    List[Any]="<s>"     ,					__UpperCAmelCase					:    Optional[int]="<unk>"     ,					__UpperCAmelCase					:    List[Any]="<pad>"     ,					__UpperCAmelCase					:    int="<mask>"     ,					__UpperCAmelCase					:    Optional[int]=None     ,					__UpperCAmelCase					:    str=None     ,					__UpperCAmelCase					:    int=None     ,					__UpperCAmelCase					:    int = None     ,					__UpperCAmelCase					:    Union[str, Any]=None     ,					__UpperCAmelCase					:    Dict=False     ,					**__UpperCAmelCase					:    Optional[int]     ,					) ->     Union[str, Any]:
						SCREAMING_SNAKE_CASE__										=   AddedToken(A_     ,					lstrip=A_     ,					rstrip=A_							) if isinstance(A_     ,					A_							) else mask_token

						SCREAMING_SNAKE_CASE__										=   {} if sp_model_kwargs is None else sp_model_kwargs
						SCREAMING_SNAKE_CASE__										=   legacy_behaviour

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

						SCREAMING_SNAKE_CASE__										=   spm.SentencePieceProcessor(**self.sp_model_kwargs							)
						self.sp_model.Load(str(A_							)							)
						SCREAMING_SNAKE_CASE__										=   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
						SCREAMING_SNAKE_CASE__										=   {'''<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
						SCREAMING_SNAKE_CASE__										=   1

						SCREAMING_SNAKE_CASE__										=   len(self.sp_model							)
						SCREAMING_SNAKE_CASE__										=   {
						    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(A_							)
						}
						SCREAMING_SNAKE_CASE__										=   {v: k for k, v in self.lang_code_to_id.items()}
						SCREAMING_SNAKE_CASE__										=   len(self.sp_model							) + len(self.lang_code_to_id							) + self.fairseq_offset

						self.fairseq_tokens_to_ids.update(self.lang_code_to_id							)
						SCREAMING_SNAKE_CASE__										=   {v: k for k, v in self.fairseq_tokens_to_ids.items()}
						SCREAMING_SNAKE_CASE__										=   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]							)

						SCREAMING_SNAKE_CASE__										=   src_lang if src_lang is not None else '''eng_Latn'''
						SCREAMING_SNAKE_CASE__										=   self.lang_code_to_id[self._src_lang]
						SCREAMING_SNAKE_CASE__										=   tgt_lang
						self.set_src_lang_special_tokens(self._src_lang							)

			def __getstate__(       self					:    str							) ->     int:
						SCREAMING_SNAKE_CASE__										=   self.__dict__.copy()
						SCREAMING_SNAKE_CASE__										=   None
						SCREAMING_SNAKE_CASE__										=   self.sp_model.serialized_model_proto()
						return state

			def __setstate__(       self					:    int     ,					__UpperCAmelCase					:    Optional[Any]							) ->     int:
						SCREAMING_SNAKE_CASE__										=   d

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

						SCREAMING_SNAKE_CASE__										=   spm.SentencePieceProcessor(**self.sp_model_kwargs							)
						self.sp_model.LoadFromSerializedProto(self.sp_model_proto							)

			@property
			def        SCREAMING_SNAKE_CASE					(       self					:    List[Any]							) ->     Dict:
						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					:    Optional[int]							) ->     str:
						return self._src_lang

			@src_lang.setter
			def        SCREAMING_SNAKE_CASE					(       self					:    Tuple     ,					__UpperCAmelCase					:    Any							) ->     None:
						SCREAMING_SNAKE_CASE__										=   new_src_lang
						self.set_src_lang_special_tokens(self._src_lang							)

			def        SCREAMING_SNAKE_CASE					(       self					:    str     ,					__UpperCAmelCase					:    List[Any]     ,					__UpperCAmelCase					:    int = None     ,					__UpperCAmelCase					:    Union[str, Any] = False							) ->     List[int]:




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

						SCREAMING_SNAKE_CASE__										=   [1] * len(self.prefix_tokens							)
						SCREAMING_SNAKE_CASE__										=   [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        SCREAMING_SNAKE_CASE					(       self					:    Dict     ,					__UpperCAmelCase					:    Optional[int]     ,					__UpperCAmelCase					:    Optional[int] = 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        SCREAMING_SNAKE_CASE					(       self					:    int     ,					__UpperCAmelCase					:    Dict     ,					__UpperCAmelCase					:    List[str] = None							) ->     List[int]:
						SCREAMING_SNAKE_CASE__										=   [self.sep_token_id]
						SCREAMING_SNAKE_CASE__										=   [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					:    List[Any]     ,					__UpperCAmelCase					:    str     ,					__UpperCAmelCase					:    List[Any]     ,					__UpperCAmelCase					:    Dict     ,					__UpperCAmelCase					:    List[Any]     ,					**__UpperCAmelCase					:    Optional[Any]							) ->     int:




						if src_lang is None or tgt_lang is None:
									raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""							)
						SCREAMING_SNAKE_CASE__										=   src_lang
						SCREAMING_SNAKE_CASE__										=   self(A_     ,					add_special_tokens=A_     ,					return_tensors=A_     ,					**A_							)
						SCREAMING_SNAKE_CASE__										=   self.convert_tokens_to_ids(A_							)
						SCREAMING_SNAKE_CASE__										=   tgt_lang_id
						return inputs

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[Any]							) ->     Optional[int]:
						SCREAMING_SNAKE_CASE__										=   {self.convert_ids_to_tokens(A_							): i for i in range(self.vocab_size							)}
						vocab.update(self.added_tokens_encoder							)
						return vocab

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

			def        SCREAMING_SNAKE_CASE					(       self					:    Tuple     ,					__UpperCAmelCase					:    Optional[Any]							) ->     Tuple:




						if token in self.fairseq_tokens_to_ids:
									return self.fairseq_tokens_to_ids[token]
						SCREAMING_SNAKE_CASE__										=   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        SCREAMING_SNAKE_CASE					(       self					:    List[Any]     ,					__UpperCAmelCase					:    Union[str, Any]							) ->     str:




						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					:    Any     ,					__UpperCAmelCase					:    int							) ->     int:
						SCREAMING_SNAKE_CASE__										=   ''''''.join(A_							).replace(A_     ,					""" """							).strip()
						return out_string

			def        SCREAMING_SNAKE_CASE					(       self					:    Any     ,					__UpperCAmelCase					:    List[str]     ,					__UpperCAmelCase					:    Optional[Any] = None							) ->     Tuple[str]:




						if not os.path.isdir(A_							):
									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""							)
									return
						SCREAMING_SNAKE_CASE__										=   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:
												SCREAMING_SNAKE_CASE__										=   self.sp_model.serialized_model_proto()
												fi.write(A_							)

						return (out_vocab_file,)

			def        SCREAMING_SNAKE_CASE					(       self					:    Union[str, Any]     ,					__UpperCAmelCase					:    Union[str, Any]     ,					__UpperCAmelCase					:    Union[str, Any] = "eng_Latn"     ,					__UpperCAmelCase					:    Union[str, Any] = None     ,					__UpperCAmelCase					:    Dict = "fra_Latn"     ,					**__UpperCAmelCase					:    str     ,					) ->     BatchEncoding:
						SCREAMING_SNAKE_CASE__										=   src_lang
						SCREAMING_SNAKE_CASE__										=   tgt_lang
						return super().prepare_seqaseq_batch(A_     ,					A_     ,					**A_							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[Any]							) ->     str:
						return self.set_src_lang_special_tokens(self.src_lang							)

			def        SCREAMING_SNAKE_CASE					(       self					:    List[str]							) ->     List[Any]:
						return self.set_tgt_lang_special_tokens(self.tgt_lang							)

			def        SCREAMING_SNAKE_CASE					(       self					:    int     ,					__UpperCAmelCase					:    Optional[Any]							) ->     None:
						SCREAMING_SNAKE_CASE__										=   self.lang_code_to_id[src_lang]
						if self.legacy_behaviour:
									SCREAMING_SNAKE_CASE__										=   []
									SCREAMING_SNAKE_CASE__										=   [self.eos_token_id, self.cur_lang_code]
						else:
									SCREAMING_SNAKE_CASE__										=   [self.cur_lang_code]
									SCREAMING_SNAKE_CASE__										=   [self.eos_token_id]





			def        SCREAMING_SNAKE_CASE					(       self					:    List[Any]     ,					__UpperCAmelCase					:    Any							) ->     None:
						SCREAMING_SNAKE_CASE__										=   self.lang_code_to_id[lang]
						if self.legacy_behaviour:
									SCREAMING_SNAKE_CASE__										=   []
									SCREAMING_SNAKE_CASE__										=   [self.eos_token_id, self.cur_lang_code]
						else:
									SCREAMING_SNAKE_CASE__										=   [self.cur_lang_code]
									SCREAMING_SNAKE_CASE__										=   [self.eos_token_id]




"""simple docstring"""




import math
import sys




def 			_lowerCAmelCase		(		_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Any   			=  ''''''
  try:
    with open(_UpperCamelCase			,					'''rb'''    ) as binary_file:
      _lowercase:      Dict   			=  binary_file.read()
    for dat in data:
      _lowercase:      List[str]   			=  f'''{dat:08b}'''
      result += curr_byte
    return result
  except OSError:
    print('''File not accessible'''    )
    sys.exit()




def 			_lowerCAmelCase		(		_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Any   			=  {'''0''': '''0''', '''1''': '''1'''}
  _lowercase			,					_lowercase:      Optional[int]   			=  '''''', ''''''
  _lowercase:      Dict   			=  len(_UpperCamelCase    )

  for i in range(len(_UpperCamelCase    )    ):
    curr_string += data_bits[i]
    if curr_string not in lexicon:
      continue

    _lowercase:      Any   			=  lexicon[curr_string]
    result += last_match_id
    _lowercase:      Optional[int]   			=  last_match_id + '''0'''

    if math.loga(_UpperCamelCase    ).is_integer():
      _lowercase:      str   			=  {}
      for curr_key in list(_UpperCamelCase    ):
        _lowercase:      List[Any]   			=  lexicon.pop(_UpperCamelCase    )
      _lowercase:      Tuple   			=  new_lex

    _lowercase:      List[Any]   			=  last_match_id + '''1'''
    index += 1
    _lowercase:      List[Any]   			=  ''''''
  return result




def 			_lowerCAmelCase		(		_UpperCamelCase			,					_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Optional[Any]   			=  8
  try:
    with open(_UpperCamelCase			,					'''wb'''    ) as opened_file:
      _lowercase:      List[Any]   			=  [
          to_write[i : i + byte_length]
          for i in range(0			,					len(_UpperCamelCase    )			,					_UpperCamelCase    )
      ]

      if len(result_byte_array[-1]    ) % byte_length == 0:
        result_byte_array.append('''10000000'''    )
      else:
        result_byte_array[-1] += "1" + "0" * (
            byte_length - len(result_byte_array[-1]    ) - 1
        )

      for elem in result_byte_array[:-1]:
        opened_file.write(int(_UpperCamelCase			,					2    ).to_bytes(1			,					byteorder='''big'''    )    )
  except OSError:
    print('''File not accessible'''    )
    sys.exit()




def 			_lowerCAmelCase		(		_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Any   			=  0
  for letter in data_bits:
    if letter == "1":
      break
    counter += 1

  _lowercase:      List[str]   			=  data_bits[counter:]
  _lowercase:      Union[str, Any]   			=  data_bits[counter + 1 :]
  return data_bits




def 			_lowerCAmelCase		(		_UpperCamelCase			,					_UpperCamelCase    ):






  """simple docstring"""



  _lowercase:      Tuple   			=  read_file_binary(_UpperCamelCase    )
  _lowercase:      Optional[Any]   			=  remove_prefix(_UpperCamelCase    )
  _lowercase:      Dict   			=  decompress_data(_UpperCamelCase    )
  write_file_binary(_UpperCamelCase			,					_UpperCamelCase    )


if __name__ == "__main__":
  compress(sys.argv[1], sys.argv[2])
