


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		(					UpperCAmelCase_		:						List[Any]					,    UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						Union[str, Any]		):




      """simple docstring"""





      a		:int									=			1.5
      a		:List[Any]									=			int(factor * num_class_images		)
      a		:Optional[Any]									=			ClipClient(
          url='''https://knn.laion.ai/knn-service'''					,    indice_name='''laion_400m'''					,    num_images=UpperCAmelCase_					,    aesthetic_weight=0.1		)

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

      while True:
            a		:str									=			client.query(text=UpperCAmelCase_		)
            if len(UpperCAmelCase_		) >= factor * num_class_images or num_images > 1E4:
                  break
            else:
                  a		:Optional[int]									=			int(factor * num_images		)
                  a		:List[str]									=			ClipClient(
                      url='''https://knn.laion.ai/knn-service'''					,    indice_name='''laion_400m'''					,    num_images=UpperCAmelCase_					,    aesthetic_weight=0.1					,    )

      a		:Dict									=			0
      a		:List[Any]									=			0
      a		:List[Any]									=			tqdm(desc='''downloading real regularization images'''					,    total=UpperCAmelCase_		)

      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:
                  a		:Union[str, Any]									=			class_images[count]
                  count += 1
                  try:
                        a		:Union[str, Any]									=			requests.get(images['''url''']		)
                        if img.status_code == 200:
                              a		:Union[str, 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		(					):




      """simple docstring"""





      a		:Optional[Any]									=			argparse.ArgumentParser(''''''					,    add_help=UpperCAmelCase_		)
      parser.add_argument('''--class_prompt'''					,    help='''text prompt to retrieve images'''					,    required=UpperCAmelCase_					,    type=UpperCAmelCase_		)
      parser.add_argument('''--class_data_dir'''					,    help='''path to save images'''					,    required=UpperCAmelCase_					,    type=UpperCAmelCase_		)
      parser.add_argument('''--num_class_images'''					,    help='''number of images to download'''					,    default=200					,    type=UpperCAmelCase_		)
      return parser.parse_args()


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









import warnings

from ...utils import is_sklearn_available, requires_backends


if is_sklearn_available():
     from scipy.stats import pearsonr, spearmanr
     from sklearn.metrics import fa_score, matthews_corrcoef


snake_case							:       List[str]										=	(
    '''This metric will be removed from the library soon, metrics should be handled with the 🤗 Evaluate '''
    '''library. You can have a look at this example script for pointers: '''
    '''https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_glue.py'''
)
def 							__lowerCamelCase		(					UpperCAmelCase_		:						List[str]					,    UpperCAmelCase_		:						Optional[Any]		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      return (preds == labels).mean()
def 							__lowerCamelCase		(					UpperCAmelCase_		:						str					,    UpperCAmelCase_		:						int		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      a		:Dict									=			simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)
      a		:Any									=			fa_score(y_true=UpperCAmelCase_					,    y_pred=UpperCAmelCase_		)
      return {
          "acc": acc,
          "f1": fa,
          "acc_and_f1": (acc + fa) / 2,
      }
def 							__lowerCamelCase		(					UpperCAmelCase_		:						Dict					,    UpperCAmelCase_		:						List[Any]		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      a		:str									=			pearsonr(UpperCAmelCase_					,    UpperCAmelCase_		)[0]
      a		:Union[str, Any]									=			spearmanr(UpperCAmelCase_					,    UpperCAmelCase_		)[0]
      return {
          "pearson": pearson_corr,
          "spearmanr": spearman_corr,
          "corr": (pearson_corr + spearman_corr) / 2,
      }
def 							__lowerCamelCase		(					UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						Dict		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      assert len(UpperCAmelCase_		) == len(UpperCAmelCase_		), F'''Predictions and labels have mismatched lengths {len(UpperCAmelCase_		)} and {len(UpperCAmelCase_		)}'''
      if task_name == "cola":
            return {"mcc": matthews_corrcoef(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "sst-2":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "mrpc":
            return acc_and_fa(UpperCAmelCase_					,    UpperCAmelCase_		)
      elif task_name == "sts-b":
            return pearson_and_spearman(UpperCAmelCase_					,    UpperCAmelCase_		)
      elif task_name == "qqp":
            return acc_and_fa(UpperCAmelCase_					,    UpperCAmelCase_		)
      elif task_name == "mnli":
            return {"mnli/acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "mnli-mm":
            return {"mnli-mm/acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "qnli":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "rte":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "wnli":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "hans":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      else:
            raise KeyError(UpperCAmelCase_		)






def 							__lowerCamelCase		(					UpperCAmelCase_		:						List[str]					,    UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						List[Any]		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      if len(UpperCAmelCase_		) != len(UpperCAmelCase_		):
            raise ValueError(F'''Predictions and labels have mismatched lengths {len(UpperCAmelCase_		)} and {len(UpperCAmelCase_		)}'''		)
      if task_name == "xnli":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      else:
            raise KeyError(UpperCAmelCase_		)





