





"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path

import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm



def 					__lowerCamelCase       (							a_					:		Union[str, Any]			,       a_					:		str			,       a_					:		Tuple							)      ->				str:
      __SCREAMING_SNAKE_CASE       :List[str]		    =  1.5
      __SCREAMING_SNAKE_CASE       :str		    =  int(factor * num_class_images							)
      __SCREAMING_SNAKE_CASE       :Union[str, Any]		    =  ClipClient(
          url='''https://knn.laion.ai/knn-service'''			,       indice_name='''laion_400m'''			,       num_images=_lowerCAmelCase			,       aesthetic_weight=0.1							)

      os.makedirs(f'''{class_data_dir}/images'''			,       exist_ok=_lowerCAmelCase							)
      if len(list(Path(f'''{class_data_dir}/images'''							).iterdir()							)							) >= num_class_images:
            return

      while True:
            __SCREAMING_SNAKE_CASE       :Optional[Any]		    =  client.query(text=_lowerCAmelCase							)
            if len(_lowerCAmelCase							) >= factor * num_class_images or num_images > 1e4:
                  break
            else:
                  __SCREAMING_SNAKE_CASE       :Dict		    =  int(factor * num_images							)
                  __SCREAMING_SNAKE_CASE       :Union[str, Any]		    =  ClipClient(
                      url='''https://knn.laion.ai/knn-service'''			,       indice_name='''laion_400m'''			,       num_images=_lowerCAmelCase			,       aesthetic_weight=0.1			,       )

      __SCREAMING_SNAKE_CASE       :Any		    =  0
      __SCREAMING_SNAKE_CASE       :Optional[int]		    =  0
      __SCREAMING_SNAKE_CASE       :List[Any]		    =  tqdm(desc='''downloading real regularization images'''			,       total=_lowerCAmelCase							)

      with open(f'''{class_data_dir}/caption.txt'''			,       '''w'''							) as fa, open(f'''{class_data_dir}/urls.txt'''			,       '''w'''							) as fa, open(
          f'''{class_data_dir}/images.txt'''			,       '''w'''							) as fa:
            while total < num_class_images:
                  __SCREAMING_SNAKE_CASE       :List[Any]		    =  class_images[count]
                  count += 1
                  try:
                        __SCREAMING_SNAKE_CASE       :Optional[Any]		    =  requests.get(images['''url''']							)
                        if img.status_code == 2_00:
                              __SCREAMING_SNAKE_CASE       :Any		    =  Image.open(BytesIO(img.content							)							)
                              with open(f'''{class_data_dir}/images/{total}.jpg'''			,       '''wb'''							) as f:
                                    f.write(img.content							)
                              fa.write(images['''caption'''] + '''\n'''							)
                              fa.write(images['''url'''] + '''\n'''							)
                              fa.write(f'''{class_data_dir}/images/{total}.jpg''' + '''\n'''							)
                              total += 1
                              pbar.update(1							)
                        else:
                              continue
                  except Exception:
                        continue
      return



def 					__lowerCamelCase       (							)      ->				List[Any]:
      __SCREAMING_SNAKE_CASE       :Tuple		    =  argparse.ArgumentParser(''''''			,       add_help=_lowerCAmelCase							)
      parser.add_argument('''--class_prompt'''			,       help='''text prompt to retrieve images'''			,       required=_lowerCAmelCase			,       type=_lowerCAmelCase							)
      parser.add_argument('''--class_data_dir'''			,       help='''path to save images'''			,       required=_lowerCAmelCase			,       type=_lowerCAmelCase							)
      parser.add_argument('''--num_class_images'''			,       help='''number of images to download'''			,       default=2_00			,       type=_lowerCAmelCase							)
      return parser.parse_args()


if __name__ == "__main__":
  lowerCamelCase_       =		parse_args()
  retrieve(args.class_prompt, args.class_data_dir, args.num_class_images)






"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowerCamelCase_       =		logging.get_logger(__name__)

lowerCamelCase_       =		{"vocab_file": "spiece.model"}

lowerCamelCase_       =		{
    "vocab_file": {
        "bert_for_seq_generation": (
            "https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model"
        ),
    }
}

lowerCamelCase_       =		{"bert_for_seq_generation": 5_1_2}






class  _SCREAMING_SNAKE_CASE(       A  ):
       SCREAMING_SNAKE_CASE_       :				str     						=  VOCAB_FILES_NAMES
       SCREAMING_SNAKE_CASE_       :				Optional[Any]     						=  PRETRAINED_VOCAB_FILES_MAP
       SCREAMING_SNAKE_CASE_       :				Optional[int]     						=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       SCREAMING_SNAKE_CASE_       :				List[int]     						=  []
       SCREAMING_SNAKE_CASE_       :				List[Any]     						=  ['''input_ids''', '''attention_mask''']




       def __init__(						self		,SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__="<s>"		,SCREAMING_SNAKE_CASE__="</s>"		,SCREAMING_SNAKE_CASE__="<unk>"		,SCREAMING_SNAKE_CASE__="<pad>"		,SCREAMING_SNAKE_CASE__="<::::>"		,SCREAMING_SNAKE_CASE__ = None		,**SCREAMING_SNAKE_CASE__		,)      ->				None:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE       :Optional[Any]		    =  {} if sp_model_kwargs is None else sp_model_kwargs

             # Add extra_ids to the special token list
             super().__init__(
                 bos_token=SCREAMING_SNAKE_CASE__		,eos_token=SCREAMING_SNAKE_CASE__		,unk_token=SCREAMING_SNAKE_CASE__		,pad_token=SCREAMING_SNAKE_CASE__		,sep_token=SCREAMING_SNAKE_CASE__		,sp_model_kwargs=self.sp_model_kwargs		,**SCREAMING_SNAKE_CASE__		,)

             __SCREAMING_SNAKE_CASE       :Dict		    =  vocab_file

             __SCREAMING_SNAKE_CASE       :Optional[Any]		    =  spm.SentencePieceProcessor(**self.sp_model_kwargs							)
             self.sp_model.Load(SCREAMING_SNAKE_CASE__							)




       @property
       def    _UpperCamelCase					(						self							)      ->				List[str]:





             """simple docstring"""






             return self.sp_model.get_piece_size()




       def    _UpperCamelCase					(						self							)      ->				int:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE       :List[Any]		    =  {self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__							): i for i in range(self.vocab_size							)}
             vocab.update(self.added_tokens_encoder							)
             return vocab




       def __getstate__(						self							)      ->				Dict:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE       :int		    =  self.__dict__.copy()
             __SCREAMING_SNAKE_CASE       :Dict		    =  None
             return state




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





             """simple docstring"""






             __SCREAMING_SNAKE_CASE       :List[str]		    =  d

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

             __SCREAMING_SNAKE_CASE       :str		    =  spm.SentencePieceProcessor(**self.sp_model_kwargs							)
             self.sp_model.Load(self.vocab_file							)




       def    _UpperCamelCase					(						self		,SCREAMING_SNAKE_CASE__							)      ->				List[str]:





             """simple docstring"""






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




       def    _UpperCamelCase					(						self		,SCREAMING_SNAKE_CASE__							)      ->				int:





             """simple docstring"""






             return self.sp_model.piece_to_id(SCREAMING_SNAKE_CASE__							)




       def    _UpperCamelCase					(						self		,SCREAMING_SNAKE_CASE__							)      ->				str:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE       :Optional[int]		    =  self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE__							)
             return token




       def    _UpperCamelCase					(						self		,SCREAMING_SNAKE_CASE__							)      ->				List[Any]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE       :int		    =  []
             __SCREAMING_SNAKE_CASE       :List[str]		    =  ''''''
             for token in tokens:
                   # make sure that special tokens are not decoded using sentencepiece model
                   if token in self.all_special_tokens:
                         out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__							) + token
                         __SCREAMING_SNAKE_CASE       :Dict		    =  []
                   else:
                         current_sub_tokens.append(SCREAMING_SNAKE_CASE__							)
             out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__							)
             return out_string.strip()




       def    _UpperCamelCase					(						self		,SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__ = None							)      ->				Tuple[str]:





             """simple docstring"""






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

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

             return (out_vocab_file,)