



'''simple docstring'''
from __future__ import annotations

from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray






def A__   (					UpperCAmelCase_  ,  UpperCAmelCase_  ,  UpperCAmelCase_ = False							):
						if radian_mode:
												return [magnitude * cos(UpperCAmelCase_							), magnitude * sin(UpperCAmelCase_							)]
						return [magnitude * cos(radians(UpperCAmelCase_							)							), magnitude * sin(radians(UpperCAmelCase_							)							)]






def A__   (					UpperCAmelCase_  ,  UpperCAmelCase_  ,  UpperCAmelCase_ = 1_0**-1							):
						_UpperCamelCase :		NDArray[floataa]			    =       cross(UpperCAmelCase_  ,  UpperCAmelCase_							)
						_UpperCamelCase :		float			    =       sum(UpperCAmelCase_							)
						return abs(UpperCAmelCase_							) < eps


if __name__ == "__main__":
					# Test to check if it works
					snake_case_			:     Optional[Any]  	=  array(
					    [
					        polar_force(7_18.4, 180 - 30),
					        polar_force(8_79.54, 45),
					        polar_force(100, -90),
					    ]
					)

					snake_case_			:     NDArray[floataa]  	=  array([[0, 0], [0, 0], [0, 0]])

					assert in_static_equilibrium(forces, location)

					# Problem 1 in image_data/2D_problems.jpg
					snake_case_			:     Any  	=  array(
					    [
					        polar_force(30 * 9.81, 15),
					        polar_force(215, 180 - 45),
					        polar_force(264, 90 - 30),
					    ]
					)

					snake_case_			:     int  	=  array([[0, 0], [0, 0], [0, 0]])

					assert in_static_equilibrium(forces, location)

					# Problem in image_data/2D_problems_1.jpg
					snake_case_			:     int  	=  array([[0, -2000], [0, -1200], [0, 15600], [0, -12400]])

					snake_case_			:     Dict  	=  array([[0, 0], [6, 0], [10, 0], [12, 0]])

					assert in_static_equilibrium(forces, location)

					import doctest

					doctest.testmod()







'''simple docstring'''
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_			:     List[Any]  	=  None


snake_case_			:     Dict  	=  logging.get_logger(__name__)


snake_case_			:     Dict  	=  {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

snake_case_			:     List[str]  	=  {
    '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_			:     str  	=  {
    'facebook/nllb-large-en-ro': 1024,
    'facebook/nllb-200-distilled-600M': 1024,
}

# fmt: off
snake_case_			:     Optional[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 							lowercase__     (							lowercase       ):
	lowercase__      =      VOCAB_FILES_NAMES
	lowercase__      =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowercase__      =      PRETRAINED_VOCAB_FILES_MAP
	lowercase__      =      ["""input_ids""", """attention_mask"""]
	lowercase__      =      NllbTokenizer

	lowercase__      =      []
	lowercase__      =      []





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







							'''simple docstring'''
							# Mask token behave like a normal word, i.e. include the space before it
							_UpperCamelCase :		Optional[int]			    =       AddedToken(lowerCamelCase__			,lstrip=lowerCamelCase__			,rstrip=lowerCamelCase__			) if isinstance(lowerCamelCase__			,lowerCamelCase__			) else mask_token
							_UpperCamelCase :		Union[str, 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__			,)

							_UpperCamelCase :		int			    =       vocab_file
							_UpperCamelCase :		int			    =       False if not self.vocab_file else True

							_UpperCamelCase :		Dict			    =       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}			)
							_UpperCamelCase :		List[str]			    =       {
							    lang_code: self.convert_tokens_to_ids(lowerCamelCase__			) for lang_code in FAIRSEQ_LANGUAGE_CODES
							}

							_UpperCamelCase :		List[str]			    =       src_lang if src_lang is not None else 'eng_Latn'
							_UpperCamelCase :		int			    =       self.convert_tokens_to_ids(self._src_lang			)
							_UpperCamelCase :		Dict			    =       tgt_lang
							self.set_src_lang_special_tokens(self._src_lang			)





	@property
	def      UpperCamelCase_  (			self :    Tuple			):







							'''simple docstring'''
							return self._src_lang





	@src_lang.setter
	def      UpperCamelCase_  (			self :    Union[str, Any]			,lowerCamelCase__ :    str			):







							'''simple docstring'''
							_UpperCamelCase :		str			    =       new_src_lang
							self.set_src_lang_special_tokens(self._src_lang			)





	def      UpperCamelCase_  (			self :    List[str]			,lowerCamelCase__ :    List[int]			,lowerCamelCase__ :    Optional[List[int]] = None			):







							'''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      UpperCamelCase_  (			self :    Dict			,lowerCamelCase__ :    List[int]			,lowerCamelCase__ :    Optional[List[int]] = None			):







							'''simple docstring'''
							_UpperCamelCase :		Dict			    =       [self.sep_token_id]
							_UpperCamelCase :		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      UpperCamelCase_  (			self :    Union[str, Any]			,lowerCamelCase__ :    str			,lowerCamelCase__ :    str			,lowerCamelCase__ :    Optional[str]			,lowerCamelCase__ :    Optional[str]			,**lowerCamelCase__ :    Dict			):







							'''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 :		Tuple			    =       src_lang
							_UpperCamelCase :		Optional[Any]			    =       self(lowerCamelCase__			,add_special_tokens=lowerCamelCase__			,return_tensors=lowerCamelCase__			,**lowerCamelCase__			)
							_UpperCamelCase :		Tuple			    =       self.convert_tokens_to_ids(lowerCamelCase__			)
							_UpperCamelCase :		str			    =       tgt_lang_id
							return inputs





	def      UpperCamelCase_  (			self :    int			,lowerCamelCase__ :    List[str]			,lowerCamelCase__ :    str = "eng_Latn"			,lowerCamelCase__ :    Optional[List[str]] = None			,lowerCamelCase__ :    str = "fra_Latn"			,**lowerCamelCase__ :    Union[str, Any]			,):







							'''simple docstring'''
							_UpperCamelCase :		Tuple			    =       src_lang
							_UpperCamelCase :		List[str]			    =       tgt_lang
							return super().prepare_seqaseq_batch(lowerCamelCase__			,lowerCamelCase__			,**lowerCamelCase__			)





	def      UpperCamelCase_  (			self :    Optional[int]			):







							'''simple docstring'''
							return self.set_src_lang_special_tokens(self.src_lang			)





	def      UpperCamelCase_  (			self :    Any			):







							'''simple docstring'''
							return self.set_tgt_lang_special_tokens(self.tgt_lang			)





	def      UpperCamelCase_  (			self :    str			,lowerCamelCase__ :    List[Any]			):







							'''simple docstring'''
							_UpperCamelCase :		int			    =       self.convert_tokens_to_ids(lowerCamelCase__			)

							if self.legacy_behaviour:
													_UpperCamelCase :		Optional[Any]			    =       []
													_UpperCamelCase :		int			    =       [self.eos_token_id, self.cur_lang_code]
							else:
													_UpperCamelCase :		List[Any]			    =       [self.cur_lang_code]
													_UpperCamelCase :		List[Any]			    =       [self.eos_token_id]

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

							_UpperCamelCase :		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      UpperCamelCase_  (			self :    int			,lowerCamelCase__ :    str			):







							'''simple docstring'''
							_UpperCamelCase :		Any			    =       self.convert_tokens_to_ids(lowerCamelCase__			)
							if self.legacy_behaviour:
													_UpperCamelCase :		Tuple			    =       []
													_UpperCamelCase :		str			    =       [self.eos_token_id, self.cur_lang_code]
							else:
													_UpperCamelCase :		Tuple			    =       [self.cur_lang_code]
													_UpperCamelCase :		Optional[Any]			    =       [self.eos_token_id]

							_UpperCamelCase :		int			    =       self.convert_ids_to_tokens(self.prefix_tokens			)
							_UpperCamelCase :		List[Any]			    =       self.convert_ids_to_tokens(self.suffix_tokens			)

							_UpperCamelCase :		Optional[int]			    =       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      UpperCamelCase_  (			self :    Any			,lowerCamelCase__ :    str			,lowerCamelCase__ :    Optional[str] = None			):







							'''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
							_UpperCamelCase :		List[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,)


