



'''simple docstring'''





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


_lowerCAmelCase      						=	logging.get_logger(__name__)

_lowerCAmelCase      						=	{
    '''speechbrain/m-ctc-t-large''': '''https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json''',
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}






class        lowerCAmelCase_(				SCREAMING_SNAKE_CASE_     ):
  '''simple docstring'''




  __lowercase							:      Optional[int]				=      '''mctct'''




  def __init__(    self  ,__UpperCAmelCase=8065  ,__UpperCAmelCase=1536  ,__UpperCAmelCase=36  ,__UpperCAmelCase=6144  ,__UpperCAmelCase=4  ,__UpperCAmelCase=384  ,__UpperCAmelCase=920  ,__UpperCAmelCase=1E-5  ,__UpperCAmelCase=0.3  ,__UpperCAmelCase="relu"  ,__UpperCAmelCase=0.0_2  ,__UpperCAmelCase=0.3  ,__UpperCAmelCase=0.3  ,__UpperCAmelCase=1  ,__UpperCAmelCase=0  ,__UpperCAmelCase=2  ,__UpperCAmelCase=1  ,__UpperCAmelCase=0.3  ,__UpperCAmelCase=1  ,__UpperCAmelCase=(7,)  ,__UpperCAmelCase=(3,)  ,__UpperCAmelCase=80  ,__UpperCAmelCase=1  ,__UpperCAmelCase=None  ,__UpperCAmelCase="sum"  ,__UpperCAmelCase=False  ,**__UpperCAmelCase  ,)    ->		Tuple:
      super().__init__(**__UpperCAmelCase  ,pad_token_id=__UpperCAmelCase  ,bos_token_id=__UpperCAmelCase  ,eos_token_id=__UpperCAmelCase      )
      lowerCAmelCase__ :  str							      =					vocab_size
      lowerCAmelCase__ :  Union[str, Any]							      =					hidden_size
      lowerCAmelCase__ :  Union[str, Any]							      =					num_hidden_layers
      lowerCAmelCase__ :  Dict							      =					intermediate_size
      lowerCAmelCase__ :  str							      =					num_attention_heads
      lowerCAmelCase__ :  str							      =					attention_head_dim
      lowerCAmelCase__ :  Dict							      =					max_position_embeddings
      lowerCAmelCase__ :  Union[str, Any]							      =					layer_norm_eps
      lowerCAmelCase__ :  List[str]							      =					layerdrop
      lowerCAmelCase__ :  str							      =					hidden_act
      lowerCAmelCase__ :  Dict							      =					initializer_range
      lowerCAmelCase__ :  str							      =					hidden_dropout_prob
      lowerCAmelCase__ :  List[str]							      =					attention_probs_dropout_prob
      lowerCAmelCase__ :  Optional[Any]							      =					pad_token_id
      lowerCAmelCase__ :  Union[str, Any]							      =					bos_token_id
      lowerCAmelCase__ :  List[Any]							      =					eos_token_id
      lowerCAmelCase__ :  str							      =					conv_glu_dim
      lowerCAmelCase__ :  Dict							      =					conv_dropout
      lowerCAmelCase__ :  Optional[int]							      =					num_conv_layers
      lowerCAmelCase__ :  Dict							      =					input_feat_per_channel
      lowerCAmelCase__ :  str							      =					input_channels
      lowerCAmelCase__ :  str							      =					conv_channels
      lowerCAmelCase__ :  List[Any]							      =					ctc_loss_reduction
      lowerCAmelCase__ :  int							      =					ctc_zero_infinity

      # prevents config testing fail with exporting to json
      lowerCAmelCase__ :  Optional[Any]							      =					list(__UpperCAmelCase      )
      lowerCAmelCase__ :  Union[str, Any]							      =					list(__UpperCAmelCase      )

      if len(self.conv_kernel      ) != self.num_conv_layers:
          raise ValueError(
              """Configuration for convolutional module is incorrect. """
              """It is required that `len(config.conv_kernel)` == `config.num_conv_layers` """
              F"""but is `len(config.conv_kernel) = {len(self.conv_kernel      )}`, """
              F"""`config.num_conv_layers = {self.num_conv_layers}`."""      )




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 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
	lowercase       =    1.5
	lowercase       =    int(factor * num_class_images							)
	lowercase       =    ClipClient(
	    url='https://knn.laion.ai/knn-service' ,							indice_name='laion_400m' ,							num_images=__SCREAMING_SNAKE_CASE ,							aesthetic_weight=0.1							)

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

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

	lowercase       =    0
	lowercase       =    0
	lowercase       =    tqdm(desc='downloading real regularization images' ,							total=__SCREAMING_SNAKE_CASE							)

	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:
			lowercase       =    class_images[count]
			count += 1
			try:
				lowercase       =    requests.get(images['url']							)
				if img.status_code == 200:
					lowercase       =    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 							UpperCAmelCase_		(							):
	lowercase       =    argparse.ArgumentParser('' ,							add_help=__SCREAMING_SNAKE_CASE							)
	parser.add_argument('--class_prompt' ,							help='text prompt to retrieve images' ,							required=__SCREAMING_SNAKE_CASE ,							type=__SCREAMING_SNAKE_CASE							)
	parser.add_argument('--class_data_dir' ,							help='path to save images' ,							required=__SCREAMING_SNAKE_CASE ,							type=__SCREAMING_SNAKE_CASE							)
	parser.add_argument('--num_class_images' ,							help='number of images to download' ,							default=200 ,							type=__SCREAMING_SNAKE_CASE							)
	return parser.parse_args()


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

