



'''simple docstring'''





from typing import List

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCamelCase											=		logging.get_logger(__name__)

_UpperCamelCase											=		{
    'snap-research/efficientformer-l1-300': (
        'https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json'
    ),
}






class    lowerCamelCase_       (							SCREAMING_SNAKE_CASE_	):
  """simple docstring"""




  a_				   ="""efficientformer"""




  def __init__(					self :      Any     ,      _a :      List[int] = [3, 2, 6, 4]     ,      _a :      List[int] = [48, 96, 224, 448]     ,      _a :      List[bool] = [True, True, True, True]     ,      _a :      int = 448     ,      _a :      int = 32     ,      _a :      int = 4     ,      _a :      int = 7     ,      _a :      int = 5     ,      _a :      int = 8     ,      _a :      int = 4     ,      _a :      float = 0.0     ,      _a :      int = 16     ,      _a :      int = 3     ,      _a :      int = 3     ,      _a :      int = 3     ,      _a :      int = 2     ,      _a :      int = 1     ,      _a :      float = 0.0     ,      _a :      int = 1     ,      _a :      bool = True     ,      _a :      bool = True     ,      _a :      float = 1e-5     ,      _a :      str = "gelu"     ,      _a :      float = 0.02     ,      _a :      float = 1e-12     ,      _a :      int = 224     ,      _a :      float = 1e-05     ,      **_a :      Dict     ,      )   ->   None:
    super().__init__(**_a  )

    __lowerCamelCase			:			List[Any]       			=					hidden_act
    __lowerCamelCase			:			List[str]       			=					hidden_dropout_prob
    __lowerCamelCase			:			Tuple       			=					hidden_sizes
    __lowerCamelCase			:			Union[str, Any]       			=					num_hidden_layers
    __lowerCamelCase			:			Dict       			=					num_attention_heads
    __lowerCamelCase			:			str       			=					initializer_range
    __lowerCamelCase			:			Optional[int]       			=					layer_norm_eps
    __lowerCamelCase			:			Dict       			=					patch_size
    __lowerCamelCase			:			List[Any]       			=					num_channels
    __lowerCamelCase			:			Tuple       			=					depths
    __lowerCamelCase			:			List[Any]       			=					mlp_expansion_ratio
    __lowerCamelCase			:			List[Any]       			=					downsamples
    __lowerCamelCase			:			Any       			=					dim
    __lowerCamelCase			:			List[Any]       			=					key_dim
    __lowerCamelCase			:			Any       			=					attention_ratio
    __lowerCamelCase			:			Any       			=					resolution
    __lowerCamelCase			:			int       			=					pool_size
    __lowerCamelCase			:			Optional[int]       			=					downsample_patch_size
    __lowerCamelCase			:			Tuple       			=					downsample_stride
    __lowerCamelCase			:			Union[str, Any]       			=					downsample_pad
    __lowerCamelCase			:			int       			=					drop_path_rate
    __lowerCamelCase			:			List[Any]       			=					num_metaad_blocks
    __lowerCamelCase			:			int       			=					distillation
    __lowerCamelCase			:			List[str]       			=					use_layer_scale
    __lowerCamelCase			:			Dict       			=					layer_scale_init_value
    __lowerCamelCase			:			Any       			=					image_size
    __lowerCamelCase			:			int       			=					batch_norm_eps











'''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 			a_	(				_lowerCAmelCase			,_lowerCAmelCase			,_lowerCAmelCase			) -> int:
  __lowerCamelCase			:			Optional[Any]       			=					1.5
  __lowerCamelCase			:			Tuple       			=					int(factor * num_class_images			)
  __lowerCamelCase			:			Tuple       			=					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:
    __lowerCamelCase			:			Dict       			=					client.query(text=_lowerCAmelCase			)
    if len(_lowerCAmelCase			) >= factor * num_class_images or num_images > 1E4:
      break
    else:
      __lowerCamelCase			:			Union[str, Any]       			=					int(factor * num_images			)
      __lowerCamelCase			:			List[str]       			=					ClipClient(
          url='https://knn.laion.ai/knn-service'			,indice_name='laion_400m'			,num_images=_lowerCAmelCase			,aesthetic_weight=0.1			,)

  __lowerCamelCase			:			List[Any]       			=					0
  __lowerCamelCase			:			Tuple       			=					0
  __lowerCamelCase			:			int       			=					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:
      __lowerCamelCase			:			List[str]       			=					class_images[count]
      count += 1
      try:
        __lowerCamelCase			:			int       			=					requests.get(images['url']			)
        if img.status_code == 200:
          __lowerCamelCase			:			str       			=					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 			a_	(				) -> Dict:
  __lowerCamelCase			:			Any       			=					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=200			,type=_lowerCAmelCase			)
  return parser.parse_args()


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






