



"""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


__snake_case				:  Any =       logging.get_logger(__name__)

__snake_case				:  Any =       '▁'

__snake_case				:  Optional[int] =       {'vocab_file': 'sentencepiece.bpe.model'}

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

__snake_case				:  List[str] =       {
    'facebook/nllb-200-distilled-600M': 1_024,
}

# fmt: off
__snake_case				:  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      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE        =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	SCREAMING_SNAKE_CASE        =      PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE        =      ['input_ids', 'attention_mask']

	SCREAMING_SNAKE_CASE        =      []
	SCREAMING_SNAKE_CASE        =      []

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

				"""simple docstring"""

				__lowerCAmelCase :    str				=			AddedToken(_SCREAMING_SNAKE_CASE			,     lstrip=_SCREAMING_SNAKE_CASE			,     rstrip=_SCREAMING_SNAKE_CASE) if isinstance(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE) else mask_token

				__lowerCAmelCase :    Tuple				=			{} if sp_model_kwargs is None else sp_model_kwargs
				__lowerCAmelCase :    Optional[Any]				=			legacy_behaviour

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

				__lowerCAmelCase :    Any				=			spm.SentencePieceProcessor(**self.sp_model_kwargs)
				self.sp_model.Load(str(_SCREAMING_SNAKE_CASE))
				__lowerCAmelCase :    List[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 :    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 :    List[str]				=			len(self.sp_model)
				__lowerCAmelCase :    Optional[Any]				=			{
				    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(_SCREAMING_SNAKE_CASE)
				}
				__lowerCAmelCase :    Union[str, Any]				=			{v: k for k, v in self.lang_code_to_id.items()}
				__lowerCAmelCase :    List[Any]				=			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 :    Optional[int]				=			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 :    List[Any]				=			src_lang if src_lang is not None else "eng_Latn"
				__lowerCAmelCase :    List[Any]				=			self.lang_code_to_id[self._src_lang]
				__lowerCAmelCase :    List[str]				=			tgt_lang
				self.set_src_lang_special_tokens(self._src_lang)

	def __getstate__(	self:						Any)							->			str:

				"""simple docstring"""

				__lowerCAmelCase :    Union[str, Any]				=			self.__dict__.copy()
				__lowerCAmelCase :    Dict				=			None
				__lowerCAmelCase :    List[Any]				=			self.sp_model.serialized_model_proto()
				return state

	def __setstate__(	self:						Optional[Any]			,     _SCREAMING_SNAKE_CASE:						List[Any])							->			Tuple:

				"""simple docstring"""

				__lowerCAmelCase :    List[Any]				=			d

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

				__lowerCAmelCase :    int				=			spm.SentencePieceProcessor(**self.sp_model_kwargs)
				self.sp_model.LoadFromSerializedProto(self.sp_model_proto)

	@property
	def 				_SCREAMING_SNAKE_CASE  (	self:						str)							->			Tuple:

				"""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:						List[Any])							->			str:

				"""simple docstring"""

				return self._src_lang

	@src_lang.setter
	def 				_SCREAMING_SNAKE_CASE  (	self:						Any			,     _SCREAMING_SNAKE_CASE:						str)							->			None:

				"""simple docstring"""

				__lowerCAmelCase :    Union[str, Any]				=			new_src_lang
				self.set_src_lang_special_tokens(self._src_lang)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Union[str, Any]			,     _SCREAMING_SNAKE_CASE:						List[int]			,     _SCREAMING_SNAKE_CASE:						Optional[List[int]] = None			,     _SCREAMING_SNAKE_CASE:						bool = False)							->			List[int]:

				"""simple docstring"""

				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 :    int				=			[1] * len(self.prefix_tokens)
				__lowerCAmelCase :    Tuple				=			[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 				_SCREAMING_SNAKE_CASE  (	self:						Optional[int]			,     _SCREAMING_SNAKE_CASE:						List[int]			,     _SCREAMING_SNAKE_CASE:						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]			,     _SCREAMING_SNAKE_CASE:						List[int]			,     _SCREAMING_SNAKE_CASE:						Optional[List[int]] = None)							->			List[int]:

				"""simple docstring"""

				__lowerCAmelCase :    Dict				=			[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]			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]			,     _SCREAMING_SNAKE_CASE:						str			,     _SCREAMING_SNAKE_CASE:						Optional[str]			,     _SCREAMING_SNAKE_CASE:						Optional[str]			,     **_SCREAMING_SNAKE_CASE:						Union[str, Any])							->			Union[str, Any]:

				"""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 :    Dict				=			src_lang
				__lowerCAmelCase :    Tuple				=			self(_SCREAMING_SNAKE_CASE			,     add_special_tokens=_SCREAMING_SNAKE_CASE			,     return_tensors=_SCREAMING_SNAKE_CASE			,     **_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    Optional[Any]				=			self.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    str				=			tgt_lang_id
				return inputs

	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[Any])							->			Optional[Any]:

				"""simple docstring"""

				__lowerCAmelCase :    Union[str, Any]				=			{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 				_SCREAMING_SNAKE_CASE  (	self:						Union[str, Any]			,     _SCREAMING_SNAKE_CASE:						str)							->			List[str]:

				"""simple docstring"""

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

	def 				_SCREAMING_SNAKE_CASE  (	self:						List[Any]			,     _SCREAMING_SNAKE_CASE:						List[Any])							->			int:

				"""simple docstring"""

				if token in self.fairseq_tokens_to_ids:
							return self.fairseq_tokens_to_ids[token]
				__lowerCAmelCase :    Optional[Any]				=			self.sp_model.PieceToId(_SCREAMING_SNAKE_CASE)

				# 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:						int			,     _SCREAMING_SNAKE_CASE:						Optional[Any])							->			Tuple:

				"""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:						int			,     _SCREAMING_SNAKE_CASE:						List[str])							->			int:

				"""simple docstring"""

				__lowerCAmelCase :    str				=			"".join(_SCREAMING_SNAKE_CASE).replace(_SCREAMING_SNAKE_CASE			,     " ").strip()
				return out_string

	def 				_SCREAMING_SNAKE_CASE  (	self:						Tuple			,     _SCREAMING_SNAKE_CASE:						str			,     _SCREAMING_SNAKE_CASE:						Optional[str] = None)							->			Tuple[str]:

				"""simple docstring"""

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

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

				return (out_vocab_file,)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[Any]			,     _SCREAMING_SNAKE_CASE:						List[str]			,     _SCREAMING_SNAKE_CASE:						str = "eng_Latn"			,     _SCREAMING_SNAKE_CASE:						Optional[List[str]] = None			,     _SCREAMING_SNAKE_CASE:						str = "fra_Latn"			,     **_SCREAMING_SNAKE_CASE:						Optional[Any]			,     )							->			BatchEncoding:

				"""simple docstring"""

				__lowerCAmelCase :    Optional[Any]				=			src_lang
				__lowerCAmelCase :    Any				=			tgt_lang
				return super().prepare_seqaseq_batch(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE			,     **_SCREAMING_SNAKE_CASE)

	def 				_SCREAMING_SNAKE_CASE  (	self:						List[str])							->			Any:

				"""simple docstring"""

				return self.set_src_lang_special_tokens(self.src_lang)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Tuple)							->			int:

				"""simple docstring"""

				return self.set_tgt_lang_special_tokens(self.tgt_lang)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[Any]			,     _SCREAMING_SNAKE_CASE:						Optional[Any])							->			None:

				"""simple docstring"""

				__lowerCAmelCase :    str				=			self.lang_code_to_id[src_lang]
				if self.legacy_behaviour:
							__lowerCAmelCase :    Optional[Any]				=			[]
							__lowerCAmelCase :    int				=			[self.eos_token_id, self.cur_lang_code]
				else:
							__lowerCAmelCase :    Any				=			[self.cur_lang_code]
							__lowerCAmelCase :    List[Any]				=			[self.eos_token_id]







	def 				_SCREAMING_SNAKE_CASE  (	self:						Union[str, Any]			,     _SCREAMING_SNAKE_CASE:						str)							->			None:

				"""simple docstring"""

				__lowerCAmelCase :    str				=			self.lang_code_to_id[lang]
				if self.legacy_behaviour:
							__lowerCAmelCase :    List[str]				=			[]
							__lowerCAmelCase :    int				=			[self.eos_token_id, self.cur_lang_code]
				else:
							__lowerCAmelCase :    Any				=			[self.cur_lang_code]
							__lowerCAmelCase :    Dict				=			[self.eos_token_id]




"""simple docstring"""






# Function to print upper half of diamond (pyramid)


def      _lowercase							(    __snake_case      )		->  Dict:
			for i in range(0   ,__snake_case      ):
						for _ in range(0   ,n - i - 1      ):  # printing spaces
									print(" "   ,end=""      )
						for _ in range(0   ,i + 1      ):  # printing stars
									print("* "   ,end=""      )
						print()


def      _lowercase							(    __snake_case      )		->  Tuple:
			for i in range(__snake_case   ,0   ,-1      ):
						for _ in range(__snake_case   ,0   ,-1      ):  # printing stars
									print("* "   ,end=""      )
						print()
						for _ in range(n - i + 1   ,0   ,-1      ):  # printing spaces
									print(" "   ,end=""      )


def      _lowercase							(    __snake_case      )		->  Any:
			if n <= 0:
						print("       ...       ....        nothing printing :("      )
						return
			floyd(__snake_case      )  # upper half
			reverse_floyd(__snake_case      )  # lower half


if __name__ == "__main__":
	print(R'| /\ | |- |  |-  |--| |\  /| |-')
	print(R'|/  \| |- |_ |_  |__| | \/ | |_')
	__snake_case				:  Tuple =       1
	while K:
		__snake_case				:  List[str] =       int(input('enter the number and , and see the magic : '))
		print()
		pretty_print(user_number)
		__snake_case				:  Optional[Any] =       int(input('press 0 to exit... and 1 to continue...'))

	print('Good Bye...')