

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


UpperCAmelCase__     = logging.get_logger(__name__)

UpperCAmelCase__     = "▁"

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

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

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

# fmt: off
UpperCAmelCase__     = ["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					(    UpperCAmelCase_		):
			UpperCamelCase           =  VOCAB_FILES_NAMES
			UpperCamelCase           =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase           =  PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase           =  ["input_ids", "attention_mask"]

			UpperCamelCase           =  []
			UpperCamelCase           =  []



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



						"""simple docstring"""






						_UpperCAmelCase	 =     AddedToken(_snake_case				,	lstrip=_snake_case				,	rstrip=_snake_case) if isinstance(_snake_case				,	_snake_case) else mask_token

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

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

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

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

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

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



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



						"""simple docstring"""






						_UpperCAmelCase	 =     self.__dict__.copy()
						_UpperCAmelCase	 =     None
						_UpperCAmelCase	 =     self.sp_model.serialized_model_proto()
						return state



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



						"""simple docstring"""






						_UpperCAmelCase	 =     d

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

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



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



						"""simple docstring"""






						return self._src_lang



			@src_lang.setter
			def 					_lowerCamelCase (		self     :						Any				,	A     :						str)     ->					Dict:



						"""simple docstring"""






						_UpperCAmelCase	 =     new_src_lang
						self.set_src_lang_special_tokens(self._src_lang)



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



						"""simple docstring"""






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

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



			def 					_lowerCamelCase (		self     :						str				,	A     :						List[int]				,	A     :						Optional[List[int]] = None)     ->					Optional[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 					_lowerCamelCase (		self     :						str				,	A     :						List[int]				,	A     :						Optional[List[int]] = None)     ->					Tuple:



						"""simple docstring"""






						_UpperCAmelCase	 =     [self.sep_token_id]
						_UpperCAmelCase	 =     [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 					_lowerCamelCase (		self     :						List[Any]				,	A     :						Any				,	A     :						str				,	A     :						Optional[str]				,	A     :						Optional[str]				,	**A     :						Optional[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')
						_UpperCAmelCase	 =     src_lang
						_UpperCAmelCase	 =     self(_snake_case				,	add_special_tokens=_snake_case				,	return_tensors=_snake_case				,	**_snake_case)
						_UpperCAmelCase	 =     self.convert_tokens_to_ids(_snake_case)
						_UpperCAmelCase	 =     tgt_lang_id
						return inputs



			def 					_lowerCamelCase (		self     :						Optional[int])     ->					int:



						"""simple docstring"""






						_UpperCAmelCase	 =     {self.convert_ids_to_tokens(_snake_case): i for i in range(self.vocab_size)}
						vocab.update(self.added_tokens_encoder)
						return vocab



			def 					_lowerCamelCase (		self     :						Any				,	A     :						str)     ->					Dict:



						"""simple docstring"""






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



			def 					_lowerCamelCase (		self     :						str				,	A     :						List[str])     ->					int:



						"""simple docstring"""






						if token in self.fairseq_tokens_to_ids:
									return self.fairseq_tokens_to_ids[token]
						_UpperCAmelCase	 =     self.sp_model.PieceToId(_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 					_lowerCamelCase (		self     :						Optional[Any]				,	A     :						List[Any])     ->					int:



						"""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 					_lowerCamelCase (		self     :						Optional[int]				,	A     :						Dict)     ->					List[Any]:



						"""simple docstring"""






						_UpperCAmelCase	 =     ''.join(_snake_case).replace(_snake_case				,	' ').strip()
						return out_string



			def 					_lowerCamelCase (		self     :						Optional[Any]				,	A     :						str				,	A     :						Optional[str] = None)     ->					Dict:



						"""simple docstring"""






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

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

						return (out_vocab_file,)



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



						"""simple docstring"""






						_UpperCAmelCase	 =     src_lang
						_UpperCAmelCase	 =     tgt_lang
						return super().prepare_seqaseq_batch(_snake_case				,	_snake_case				,	**_snake_case)



			def 					_lowerCamelCase (		self     :						int)     ->					Any:



						"""simple docstring"""






						return self.set_src_lang_special_tokens(self.src_lang)



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



						"""simple docstring"""






						return self.set_tgt_lang_special_tokens(self.tgt_lang)



			def 					_lowerCamelCase (		self     :						List[str]				,	A     :						Tuple)     ->					List[str]:



						"""simple docstring"""






						_UpperCAmelCase	 =     self.lang_code_to_id[src_lang]
						if self.legacy_behaviour:
									_UpperCAmelCase	 =     []
									_UpperCAmelCase	 =     [self.eos_token_id, self.cur_lang_code]
						else:
									_UpperCAmelCase	 =     [self.cur_lang_code]
									_UpperCAmelCase	 =     [self.eos_token_id]



			def 					_lowerCamelCase (		self     :						List[Any]				,	A     :						str)     ->					Optional[Any]:



						"""simple docstring"""






						_UpperCAmelCase	 =     self.lang_code_to_id[lang]
						if self.legacy_behaviour:
									_UpperCAmelCase	 =     []
									_UpperCAmelCase	 =     [self.eos_token_id, self.cur_lang_code]
						else:
									_UpperCAmelCase	 =     [self.cur_lang_code]
									_UpperCAmelCase	 =     [self.eos_token_id]





import os

# Precomputes a list of the 100 first triangular numbers
UpperCAmelCase__     = [int(0.5 * n * (n + 1)) for n in range(1, 101)]





def 							A			(  )       ->				List[str]:







			'''simple docstring'''
			_UpperCAmelCase	 =     os.path.dirname(os.path.realpath(_UpperCAmelCase					)					)
			_UpperCAmelCase	 =     os.path.join(_UpperCAmelCase							,     'words.txt'					)

			_UpperCAmelCase	 =     ''
			with open(_UpperCAmelCase					) as f:
						_UpperCAmelCase	 =     f.readline()

			_UpperCAmelCase	 =     [word.strip('"'					) for word in words.strip('\r\n'					).split(','					)]
			_UpperCAmelCase	 =     [
			    word
			    for word in [sum(ord(_UpperCAmelCase					) - 64 for x in word					) for word in words]
			    if word in TRIANGULAR_NUMBERS
			]
			return len(_UpperCAmelCase					)


if __name__ == "__main__":
							print(solution())
