


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							:	Dict					      =				logging.get_logger(__name__)

snake_case							:	List[str]					      =				'''▁'''

snake_case							:	int					      =				{'''vocab_file''': '''sentencepiece.bpe.model'''}

snake_case							:	List[Any]					      =				{
    '''vocab_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'''
        ),
    }
}

snake_case							:	Optional[Any]					      =				{
    '''facebook/nllb-200-distilled-600M''': 10_24,
}

# fmt: off
snake_case							:	str					      =				['''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 	snake_case_       (lowerCamelCase_				):
					UpperCAmelCase__ :   Dict   				=      VOCAB_FILES_NAMES
					UpperCAmelCase__ :   Dict   				=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					UpperCAmelCase__ :   Optional[Any]   				=      PRETRAINED_VOCAB_FILES_MAP
					UpperCAmelCase__ :   Dict   				=      ['''input_ids''', '''attention_mask''']

					UpperCAmelCase__ :   List[int]   				=      []
					UpperCAmelCase__ :   List[int]   				=      []
					def __init__(				self       :str      ,__snake_case       :int      ,__snake_case       :Optional[Any]="<s>"      ,__snake_case       :int="</s>"      ,__snake_case       :Tuple="</s>"      ,__snake_case       :List[Any]="<s>"      ,__snake_case       :List[str]="<unk>"      ,__snake_case       :str="<pad>"      ,__snake_case       :List[Any]="<mask>"      ,__snake_case       :Optional[int]=None      ,__snake_case       :Tuple=None      ,__snake_case       :List[str]=None      ,__snake_case       :Optional[Dict[str, Any]] = None      ,__snake_case       :Optional[Any]=None      ,__snake_case       :str=False      ,**__snake_case       :str      ,) ->   str:
												# Mask token behave like a normal word, i.e. include the space before it
												a__					=					AddedToken(__snake_case      ,lstrip=__snake_case      ,rstrip=__snake_case				) if isinstance(__snake_case      ,__snake_case				) else mask_token

												a__					=					{} if sp_model_kwargs is None else sp_model_kwargs
												a__					=					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      ,)

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

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

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

												a__					=					src_lang if src_lang is not None else 'eng_Latn'
												a__					=					self.lang_code_to_id[self._src_lang]
												a__					=					tgt_lang
												self.set_src_lang_special_tokens(self._src_lang				)
					def __getstate__(				self       :Any				) ->   Optional[int]:
												a__					=					self.__dict__.copy()
												a__					=					None
												a__					=					self.sp_model.serialized_model_proto()
												return state
					def __setstate__(				self       :Optional[Any]      ,__snake_case       :int				) ->   int:
												a__					=					d

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

												a__					=					spm.SentencePieceProcessor(**self.sp_model_kwargs				)
												self.sp_model.LoadFromSerializedProto(self.sp_model_proto				)
					@property
					def 			lowerCamelCase__(				self       :List[Any]				) ->   int:
												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       :Optional[Any]				) ->   str:
												return self._src_lang
					@src_lang.setter
					def 			lowerCamelCase__(				self       :int      ,__snake_case       :str				) ->   None:
												a__					=					new_src_lang
												self.set_src_lang_special_tokens(self._src_lang				)
					def 			lowerCamelCase__(				self       :int      ,__snake_case       :List[int]      ,__snake_case       :Optional[List[int]] = None      ,__snake_case       :bool = False				) ->   List[int]:

												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				)

												a__					=					[1] * len(self.prefix_tokens				)
												a__					=					[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       :List[str]      ,__snake_case       :List[int]      ,__snake_case       :Optional[List[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 			lowerCamelCase__(				self       :Dict      ,__snake_case       :List[int]      ,__snake_case       :Optional[List[int]] = None				) ->   List[int]:
												a__					=					[self.sep_token_id]
												a__					=					[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       :Tuple      ,__snake_case       :Any      ,__snake_case       :str      ,__snake_case       :Optional[str]      ,__snake_case       :Optional[str]      ,**__snake_case       :str				) ->   Optional[Any]:
												if src_lang is None or tgt_lang is None:
																			raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'				)
												a__					=					src_lang
												a__					=					self(__snake_case      ,add_special_tokens=__snake_case      ,return_tensors=__snake_case      ,**__snake_case				)
												a__					=					self.convert_tokens_to_ids(__snake_case				)
												a__					=					tgt_lang_id
												return inputs
					def 			lowerCamelCase__(				self       :Optional[int]				) ->   Optional[Any]:
												a__					=					{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      ,__snake_case       :str				) ->   List[str]:
												return self.sp_model.encode(__snake_case      ,out_type=__snake_case				)
					def 			lowerCamelCase__(				self       :int      ,__snake_case       :str				) ->   List[str]:
												if token in self.fairseq_tokens_to_ids:
																			return self.fairseq_tokens_to_ids[token]
												a__					=					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       :Union[str, Any]      ,__snake_case       :int				) ->   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 			lowerCamelCase__(				self       :Optional[Any]      ,__snake_case       :Tuple				) ->   Optional[Any]:
												a__					=					''.join(__snake_case				).replace(__snake_case      ,' '				).strip()
												return out_string
					def 			lowerCamelCase__(				self       :Dict      ,__snake_case       :str      ,__snake_case       :Optional[str] = None				) ->   Tuple[str]:
												if not os.path.isdir(__snake_case				):
																			logger.error(F'Vocabulary path ({save_directory}) should be a directory'				)
																			return
												a__					=					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:
																										a__					=					self.sp_model.serialized_model_proto()
																										fi.write(__snake_case				)

												return (out_vocab_file,)
					def 			lowerCamelCase__(				self       :str      ,__snake_case       :List[str]      ,__snake_case       :str = "eng_Latn"      ,__snake_case       :Optional[List[str]] = None      ,__snake_case       :str = "fra_Latn"      ,**__snake_case       :Any      ,) ->   BatchEncoding:
												a__					=					src_lang
												a__					=					tgt_lang
												return super().prepare_seqaseq_batch(__snake_case      ,__snake_case      ,**__snake_case				)
					def 			lowerCamelCase__(				self       :Optional[Any]				) ->   List[str]:
												return self.set_src_lang_special_tokens(self.src_lang				)
					def 			lowerCamelCase__(				self       :str				) ->   str:
												return self.set_tgt_lang_special_tokens(self.tgt_lang				)
					def 			lowerCamelCase__(				self       :Union[str, Any]      ,__snake_case       :Any				) ->   None:
												a__					=					self.lang_code_to_id[src_lang]
												if self.legacy_behaviour:
																			a__					=					[]
																			a__					=					[self.eos_token_id, self.cur_lang_code]
												else:
																			a__					=					[self.cur_lang_code]
																			a__					=					[self.eos_token_id]



					def 			lowerCamelCase__(				self       :int      ,__snake_case       :str				) ->   None:
												a__					=					self.lang_code_to_id[lang]
												if self.legacy_behaviour:
																			a__					=					[]
																			a__					=					[self.eos_token_id, self.cur_lang_code]
												else:
																			a__					=					[self.cur_lang_code]
																			a__					=					[self.eos_token_id]





from collections import defaultdict
from math import ceil, sqrt






def 							__lowercase       (			__lowerCAmelCase							:    int = 1_0_0_0_0_0_0 ,   __lowerCAmelCase							:    int = 1_0       ):
							a__					=					defaultdict(__lowerCAmelCase       )

							for outer_width in range(3 ,   (t_limit // 4) + 2       ):
														if outer_width * outer_width > t_limit:
																					a__					=					max(
																					    ceil(sqrt(outer_width * outer_width - t_limit       )       ) ,   1       )
														else:
																					a__					=					1

														hole_width_lower_bound += (outer_width - hole_width_lower_bound) % 2

														for hole_width in range(__lowerCAmelCase ,   outer_width - 1 ,   2       ):
																					count[outer_width * outer_width - hole_width * hole_width] += 1

							return sum(1 for n in count.values() if 1 <= n <= 1_0       )


if __name__ == "__main__":
						print(f"""{solution() = }""")




