



"""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


lowerCamelCase       	=       logging.get_logger(__name__)

lowerCamelCase       	=       '▁'

lowerCamelCase       	=       {'vocab_file': 'sentencepiece.bpe.model'}

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

lowerCamelCase       	=       {
    'facebook/nllb-200-distilled-600M': 1_024,
}

# fmt: off
lowerCamelCase       	=       ['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__       (   _lowerCamelCase				):







       '''simple docstring'''


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

       UpperCamelCase						=					[]
       UpperCamelCase						=					[]



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


             '''simple docstring'''




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

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

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

             UpperCAmelCase_      			=							spm.SentencePieceProcessor(**self.sp_model_kwargs   )
             self.sp_model.Load(str(_UpperCAmelCase   )   )
             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(_UpperCAmelCase   )
             }
             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      :  str   )			->						str:


             '''simple docstring'''




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



       def __setstate__(							self      :  int		,    _UpperCAmelCase      :  Optional[int]   )			->						Optional[int]:


             '''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 					lowercase__    (							self      :  Any   )			->						int:


             '''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 					lowercase__    (							self      :  str   )			->						Optional[Any]:


             '''simple docstring'''




             return self._src_lang



       @src_lang.setter
       def 					lowercase__    (							self      :  Any		,    _UpperCAmelCase      :  str   )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							new_src_lang
             self.set_src_lang_special_tokens(self._src_lang   )



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


             '''simple docstring'''




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

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



       def 					lowercase__    (							self      :  Optional[int]		,    _UpperCAmelCase      :  List[int]		,    _UpperCAmelCase      :  Optional[List[int]] = None   )			->						List[str]:


             '''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 					lowercase__    (							self      :  str		,    _UpperCAmelCase      :  List[int]		,    _UpperCAmelCase      :  Optional[List[int]] = None   )			->						Union[str, Any]:


             '''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 					lowercase__    (							self      :  int		,    _UpperCAmelCase      :  List[str]		,    _UpperCAmelCase      :  str		,    _UpperCAmelCase      :  Optional[str]		,    _UpperCAmelCase      :  Optional[str]		,    **_UpperCAmelCase      :  Union[str, Any]   )			->						int:


             '''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(_UpperCAmelCase		,    add_special_tokens=_UpperCAmelCase		,    return_tensors=_UpperCAmelCase		,    **_UpperCAmelCase   )
             UpperCAmelCase_      			=							self.convert_tokens_to_ids(_UpperCAmelCase   )
             UpperCAmelCase_      			=							tgt_lang_id
             return inputs



       def 					lowercase__    (							self      :  Any   )			->						Tuple:


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  int		,    _UpperCAmelCase      :  str   )			->						Any:


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  List[str]		,    _UpperCAmelCase      :  Union[str, Any]   )			->						Optional[Any]:


             '''simple docstring'''




             if token in self.fairseq_tokens_to_ids:
                   return self.fairseq_tokens_to_ids[token]
             UpperCAmelCase_      			=							self.sp_model.PieceToId(_UpperCAmelCase   )

             # 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 					lowercase__    (							self      :  int		,    _UpperCAmelCase      :  Tuple   )			->						List[str]:


             '''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 					lowercase__    (							self      :  Dict		,    _UpperCAmelCase      :  Union[str, Any]   )			->						Dict:


             '''simple docstring'''




             UpperCAmelCase_      			=							"".join(_UpperCAmelCase   ).replace(_UpperCAmelCase		,    " "   ).strip()
             return out_string



       def 					lowercase__    (							self      :  List[str]		,    _UpperCAmelCase      :  str		,    _UpperCAmelCase      :  Optional[str] = None   )			->						Union[str, Any]:


             '''simple docstring'''




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

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

             return (out_vocab_file,)



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


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  Tuple   )			->						List[Any]:


             '''simple docstring'''




             return self.set_src_lang_special_tokens(self.src_lang   )



       def 					lowercase__    (							self      :  Tuple   )			->						List[Any]:


             '''simple docstring'''




             return self.set_tgt_lang_special_tokens(self.tgt_lang   )



       def 					lowercase__    (							self      :  Any		,    _UpperCAmelCase      :  Union[str, Any]   )			->						Dict:


             '''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 					lowercase__    (							self      :  Dict		,    _UpperCAmelCase      :  str   )			->						Union[str, 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]









"""simple docstring"""





import glob
import os
import random
from string import ascii_lowercase, digits

import cva
lowerCamelCase       	=						""""""
lowerCamelCase       	=						""""""
lowerCamelCase       	=						""""""
lowerCamelCase       	=						1  # (0 is vertical, 1 is horizontal)
def        a__     (				):
      UpperCAmelCase_			,   UpperCAmelCase_      			=							get_dataset(lowerCAmelCase__     ,      lowerCAmelCase__				)
      print("Processing..."				)
      UpperCAmelCase_			,   UpperCAmelCase_			,   UpperCAmelCase_      			=							update_image_and_anno(lowerCAmelCase__     ,      lowerCAmelCase__     ,      lowerCAmelCase__				)

      for index, image in enumerate(lowerCAmelCase__				):
            # Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
            UpperCAmelCase_      			=							random_chars(32				)
            UpperCAmelCase_      			=							paths[index].split(os.sep				)[-1].rsplit("."     ,      1				)[0]
            UpperCAmelCase_      			=							f"""{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}"""
            cva.imwrite(f"""/{file_root}.jpg"""     ,      lowerCAmelCase__     ,      [cva.IMWRITE_JPEG_QUALITY, 85]				)
            print(f"""Success {index+1}/{len(lowerCAmelCase__				)} with {file_name}"""				)
            UpperCAmelCase_      			=							[]
            for anno in new_annos[index]:
                  UpperCAmelCase_      			=							f"""{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}"""
                  annos_list.append(lowerCAmelCase__				)
            with open(f"""/{file_root}.txt"""     ,      "w"				) as outfile:
                  outfile.write("\n".join(line for line in annos_list				)				)
def        a__     (				lowerCAmelCase__     ,      lowerCAmelCase__				):
      UpperCAmelCase_      			=							[]
      UpperCAmelCase_      			=							[]
      for label_file in glob.glob(os.path.join(lowerCAmelCase__     ,      "*.txt"				)				):
            UpperCAmelCase_      			=							label_file.split(os.sep				)[-1].rsplit("."     ,      1				)[0]
            with open(lowerCAmelCase__				) as in_file:
                  UpperCAmelCase_      			=							in_file.readlines()
            UpperCAmelCase_      			=							os.path.join(lowerCAmelCase__     ,      f"""{label_name}.jpg"""				)

            UpperCAmelCase_      			=							[]
            for obj_list in obj_lists:
                  UpperCAmelCase_      			=							obj_list.rstrip("\n"				).split(" "				)
                  boxes.append(
                      [
                          int(obj[0]				),
                          float(obj[1]				),
                          float(obj[2]				),
                          float(obj[3]				),
                          float(obj[4]				),
                      ]				)
            if not boxes:
                  continue
            img_paths.append(lowerCAmelCase__				)
            labels.append(lowerCAmelCase__				)
      return img_paths, labels
def        a__     (				lowerCAmelCase__     ,      lowerCAmelCase__     ,      lowerCAmelCase__ = 1				):
      UpperCAmelCase_      			=							[]
      UpperCAmelCase_      			=							[]
      UpperCAmelCase_      			=							[]
      for idx in range(len(lowerCAmelCase__				)				):
            UpperCAmelCase_      			=							[]
            UpperCAmelCase_      			=							img_list[idx]
            path_list.append(lowerCAmelCase__				)
            UpperCAmelCase_      			=							anno_list[idx]
            UpperCAmelCase_      			=							cva.imread(lowerCAmelCase__				)
            if flip_type == 1:
                  UpperCAmelCase_      			=							cva.flip(lowerCAmelCase__     ,      lowerCAmelCase__				)
                  for bbox in img_annos:
                        UpperCAmelCase_      			=							1 - bbox[1]
                        new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]				)
            elif flip_type == 0:
                  UpperCAmelCase_      			=							cva.flip(lowerCAmelCase__     ,      lowerCAmelCase__				)
                  for bbox in img_annos:
                        UpperCAmelCase_      			=							1 - bbox[2]
                        new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]				)
            new_annos_lists.append(lowerCAmelCase__				)
            new_imgs_list.append(lowerCAmelCase__				)
      return new_imgs_list, new_annos_lists, path_list
def        a__     (				lowerCAmelCase__ = 32				):
      assert number_char > 1, "The number of character should greater than 1"
      UpperCAmelCase_      			=							ascii_lowercase + digits
      return "".join(random.choice(lowerCAmelCase__				) for _ in range(lowerCAmelCase__				)				)


if __name__ == "__main__":
  main()
  print("""DONE ✅""")




