



import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
							from .tokenization_nllb import NllbTokenizer
else:
							__snake_case       :	Tuple            =None


__snake_case       :	int            =logging.get_logger(__name__)


__snake_case       :	int            ={'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

__snake_case       :	Optional[int]            ={
    '''vocab_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/tokenizer.json'''
        ),
    },
}

__snake_case       :	int            ={
    '''facebook/nllb-large-en-ro''': 1_0_2_4,
    '''facebook/nllb-200-distilled-600M''': 1_0_2_4,
}

# fmt: off
__snake_case       :	List[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__    (							a__):




		'''simple docstring'''



		snake_case_			=VOCAB_FILES_NAMES
		snake_case_			=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		snake_case_			=PRETRAINED_VOCAB_FILES_MAP
		snake_case_			=["""input_ids""", """attention_mask"""]
		snake_case_			=NllbTokenizer

		snake_case_			=[]
		snake_case_			=[]



		def __init__(self	,__lowerCamelCase=None	,__lowerCamelCase=None	,__lowerCamelCase="<s>"	,__lowerCamelCase="</s>"	,__lowerCamelCase="</s>"	,__lowerCamelCase="<s>"	,__lowerCamelCase="<unk>"	,__lowerCamelCase="<pad>"	,__lowerCamelCase="<mask>"	,__lowerCamelCase=None	,__lowerCamelCase=None	,__lowerCamelCase=None	,__lowerCamelCase=False	,**__lowerCamelCase	,)  ->    Optional[Any]:

						"""simple docstring"""






						lowerCAmelCase__  :       Dict				=  AddedToken(lowerCAmelCase__	,lstrip=lowerCAmelCase__	,rstrip=lowerCAmelCase__				) if isinstance(lowerCAmelCase__	,lowerCAmelCase__				) else mask_token
						lowerCAmelCase__  :       Optional[Any]				=  legacy_behaviour
						super().__init__(
						    vocab_file=lowerCAmelCase__	,tokenizer_file=lowerCAmelCase__	,bos_token=lowerCAmelCase__	,eos_token=lowerCAmelCase__	,sep_token=lowerCAmelCase__	,cls_token=lowerCAmelCase__	,unk_token=lowerCAmelCase__	,pad_token=lowerCAmelCase__	,mask_token=lowerCAmelCase__	,src_lang=lowerCAmelCase__	,tgt_lang=lowerCAmelCase__	,additional_special_tokens=lowerCAmelCase__	,legacy_behaviour=lowerCAmelCase__	,**lowerCAmelCase__	,)

						lowerCAmelCase__  :       int				=  vocab_file
						lowerCAmelCase__  :       Any				=  False if not self.vocab_file else True

						lowerCAmelCase__  :       List[str]				=  FAIRSEQ_LANGUAGE_CODES.copy()

						if additional_special_tokens is not None:
										# Only add those special tokens if they are not already there.
										_additional_special_tokens.extend(
										    [t for t in additional_special_tokens if t not in _additional_special_tokens]				)

						self.add_special_tokens({'''additional_special_tokens''': _additional_special_tokens}				)
						lowerCAmelCase__  :       str				=  {
						    lang_code: self.convert_tokens_to_ids(lowerCAmelCase__				) for lang_code in FAIRSEQ_LANGUAGE_CODES
						}

						lowerCAmelCase__  :       List[Any]				=  src_lang if src_lang is not None else "eng_Latn"
						lowerCAmelCase__  :       str				=  self.convert_tokens_to_ids(self._src_lang				)
						lowerCAmelCase__  :       Any				=  tgt_lang
						self.set_src_lang_special_tokens(self._src_lang				)



		@property
		def 	lowerCAmelCase__   (self				)  ->    str:

						"""simple docstring"""






						return self._src_lang



		@src_lang.setter
		def 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    None:

						"""simple docstring"""






						lowerCAmelCase__  :       List[str]				=  new_src_lang
						self.set_src_lang_special_tokens(self._src_lang				)



		def 	lowerCAmelCase__   (self	,__lowerCamelCase	,__lowerCamelCase = 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 	lowerCAmelCase__   (self	,__lowerCamelCase	,__lowerCamelCase = None				)  ->    List[int]:

						"""simple docstring"""






						lowerCAmelCase__  :       str				=  [self.sep_token_id]
						lowerCAmelCase__  :       Union[str, Any]				=  [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	,__lowerCamelCase	,__lowerCamelCase	,__lowerCamelCase	,__lowerCamelCase	,**__lowerCamelCase				)  ->    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__  :       int				=  self(lowerCAmelCase__	,add_special_tokens=lowerCAmelCase__	,return_tensors=lowerCAmelCase__	,**lowerCAmelCase__				)
						lowerCAmelCase__  :       Dict				=  self.convert_tokens_to_ids(lowerCAmelCase__				)
						lowerCAmelCase__  :       Any				=  tgt_lang_id
						return inputs



		def 	lowerCAmelCase__   (self	,__lowerCamelCase	,__lowerCamelCase = "eng_Latn"	,__lowerCamelCase = None	,__lowerCamelCase = "fra_Latn"	,**__lowerCamelCase	,)  ->    BatchEncoding:

						"""simple docstring"""






						lowerCAmelCase__  :       Optional[int]				=  src_lang
						lowerCAmelCase__  :       int				=  tgt_lang
						return super().prepare_seqaseq_batch(lowerCAmelCase__	,lowerCAmelCase__	,**lowerCAmelCase__				)



		def 	lowerCAmelCase__   (self				)  ->    Tuple:

						"""simple docstring"""






						return self.set_src_lang_special_tokens(self.src_lang				)



		def 	lowerCAmelCase__   (self				)  ->    str:

						"""simple docstring"""






						return self.set_tgt_lang_special_tokens(self.tgt_lang				)



		def 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    None:

						"""simple docstring"""






						lowerCAmelCase__  :       int				=  self.convert_tokens_to_ids(lowerCAmelCase__				)

						if self.legacy_behaviour:
										lowerCAmelCase__  :       Tuple				=  []
										lowerCAmelCase__  :       List[str]				=  [self.eos_token_id, self.cur_lang_code]
						else:
										lowerCAmelCase__  :       int				=  [self.cur_lang_code]
										lowerCAmelCase__  :       int				=  [self.eos_token_id]

						lowerCAmelCase__  :       Union[str, Any]				=  self.convert_ids_to_tokens(self.prefix_tokens				)
						lowerCAmelCase__  :       Any				=  self.convert_ids_to_tokens(self.suffix_tokens				)

						lowerCAmelCase__  :       Any				=  processors.TemplateProcessing(
						    single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str	,pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str	,special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str	,self.prefix_tokens + self.suffix_tokens				)				)	,)



		def 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    None:

						"""simple docstring"""






						lowerCAmelCase__  :       str				=  self.convert_tokens_to_ids(lowerCAmelCase__				)
						if self.legacy_behaviour:
										lowerCAmelCase__  :       Optional[Any]				=  []
										lowerCAmelCase__  :       int				=  [self.eos_token_id, self.cur_lang_code]
						else:
										lowerCAmelCase__  :       List[Any]				=  [self.cur_lang_code]
										lowerCAmelCase__  :       List[Any]				=  [self.eos_token_id]

						lowerCAmelCase__  :       int				=  self.convert_ids_to_tokens(self.prefix_tokens				)
						lowerCAmelCase__  :       int				=  self.convert_ids_to_tokens(self.suffix_tokens				)

						lowerCAmelCase__  :       Any				=  processors.TemplateProcessing(
						    single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str	,pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str	,special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str	,self.prefix_tokens + self.suffix_tokens				)				)	,)



		def 	lowerCAmelCase__   (self	,__lowerCamelCase	,__lowerCamelCase = None				)  ->    Tuple[str]:

						"""simple docstring"""






						if not self.can_save_slow_tokenizer:
										raise ValueError(
										    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
										    '''tokenizer.'''				)

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

						if os.path.abspath(self.vocab_file				) != os.path.abspath(lowerCAmelCase__				):
										copyfile(self.vocab_file	,lowerCAmelCase__				)

						return (out_vocab_file,)






from typing import Dict

import numpy as np
import torch

from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map






def 			lowerCAmelCase__	(					lowerCamelCase_	:	Dict[str, torch.Tensor]):





				'''simple docstring'''

				lowerCAmelCase__  :       List[Any]				=  []
				lowerCAmelCase__  :       int				=  []
				lowerCAmelCase__  :       Optional[int]				=  []

				for rt in rc.restypes:
								lowerCAmelCase__  :       int				=  rc.restype_name_to_atomaa_names[rc.restype_atoa[rt]]
								restype_atomaa_to_atomaa_list.append([(rc.atom_order[name] if name else 0) for name in atom_names])
								lowerCAmelCase__  :       Any				=  {name: i for i, name in enumerate(lowerCamelCase_)}
								restype_atomaa_to_atomaa_list.append(
								    [(atom_name_to_idxaa[name] if name in atom_name_to_idxaa else 0) for name in rc.atom_types])

								restype_atomaa_mask_list.append([(1.0 if name else 0.0) for name in atom_names])

				# Add dummy mapping for restype 'UNK'
				restype_atomaa_to_atomaa_list.append([0] * 14)
				restype_atomaa_to_atomaa_list.append([0] * 37)
				restype_atomaa_mask_list.append([0.0] * 14)

				lowerCAmelCase__  :       Optional[Any]				=  torch.tensor(
				    lowerCamelCase_ ,dtype=torch.intaa ,device=protein['''aatype'''].device ,)
				lowerCAmelCase__  :       Optional[int]				=  torch.tensor(
				    lowerCamelCase_ ,dtype=torch.intaa ,device=protein['''aatype'''].device ,)
				lowerCAmelCase__  :       List[str]				=  torch.tensor(
				    lowerCamelCase_ ,dtype=torch.floataa ,device=protein['''aatype'''].device ,)
				lowerCAmelCase__  :       Optional[Any]				=  protein['''aatype'''].to(torch.long)

				# create the mapping for (residx, atom14) --> atom37, i.e. an array
				# with shape (num_res, 14) containing the atom37 indices for this protein
				lowerCAmelCase__  :       Optional[int]				=  restype_atomaa_to_atomaa[protein_aatype]
				lowerCAmelCase__  :       List[str]				=  restype_atomaa_mask[protein_aatype]

				lowerCAmelCase__  :       Tuple				=  residx_atomaa_mask
				lowerCAmelCase__  :       Dict				=  residx_atomaa_to_atomaa.long()

				# create the gather indices for mapping back
				lowerCAmelCase__  :       Union[str, Any]				=  restype_atomaa_to_atomaa[protein_aatype]
				lowerCAmelCase__  :       int				=  residx_atomaa_to_atomaa.long()

				# create the corresponding mask
				lowerCAmelCase__  :       List[str]				=  torch.zeros([21, 37] ,dtype=torch.floataa ,device=protein['''aatype'''].device)
				for restype, restype_letter in enumerate(rc.restypes):
								lowerCAmelCase__  :       List[str]				=  rc.restype_atoa[restype_letter]
								lowerCAmelCase__  :       List[str]				=  rc.residue_atoms[restype_name]
								for atom_name in atom_names:
												lowerCAmelCase__  :       List[Any]				=  rc.atom_order[atom_name]
												lowerCAmelCase__  :       Any				=  1

				lowerCAmelCase__  :       int				=  restype_atomaa_mask[protein_aatype]
				lowerCAmelCase__  :       int				=  residx_atomaa_mask

				return protein






def 			lowerCAmelCase__	(					lowerCamelCase_	:	Dict[str, torch.Tensor]):





				'''simple docstring'''

				lowerCAmelCase__  :       Optional[Any]				=  tree_map(lambda lowerCamelCase_: torch.tensor(lowerCamelCase_ ,device=batch['''aatype'''].device) ,lowerCamelCase_ ,np.ndarray)
				lowerCAmelCase__  :       Union[str, Any]				=  tensor_tree_map(lambda lowerCamelCase_: np.array(lowerCamelCase_) ,make_atomaa_masks(lowerCamelCase_))
				return out

