

"""simple docstring"""





import argparse

from transformers import CanineConfig, CanineModel, CanineTokenizer, load_tf_weights_in_canine
from transformers.utils import logging


logging.set_verbosity_info()




def 						_A						(						UpperCamelCase_  : List[Any],    UpperCamelCase_  : Any)			->		Optional[int]:
   '''simple docstring'''


   __lowercase			=		CanineConfig()
   __lowercase			=		CanineModel(UpperCamelCase_)
   model.eval()

   print(F"""Building PyTorch model from configuration: {config}""")

   # Load weights from tf checkpoint
   load_tf_weights_in_canine(UpperCamelCase_,    UpperCamelCase_,    UpperCamelCase_)

   # Save pytorch-model (weights and configuration)
   print(F"""Save PyTorch model to {pytorch_dump_path}""")
   model.save_pretrained(UpperCamelCase_)

   # Save tokenizer files
   __lowercase			=		CanineTokenizer()
   print(F"""Save tokenizer files to {pytorch_dump_path}""")
   tokenizer.save_pretrained(UpperCamelCase_)


if __name__ == "__main__":
   _a				   =							argparse.ArgumentParser()
   # Required parameters
   parser.add_argument(
       '--tf_checkpoint_path',
       default=None,
       type=str,
       required=True,
       help='Path to the TensorFlow checkpoint. Should end with model.ckpt',
   )
   parser.add_argument(
       '--pytorch_dump_path',
       default=None,
       type=str,
       required=True,
       help='Path to a folder where the PyTorch model will be placed.',
   )
   _a				   =							parser.parse_args()
   convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)




"""simple docstring"""





import shutil

import requests




def 						_A						(						UpperCamelCase_  : str,    UpperCamelCase_  : bool = False,    UpperCamelCase_  : str = ".")			->		dict:
   '''simple docstring'''


   __lowercase			=		"https://api.nasa.gov/planetary/apod"
   return requests.get(UpperCamelCase_,    params={"api_key": api_key}).json()




def 						_A						(						UpperCamelCase_  : str,    UpperCamelCase_  : str = ".")			->		dict:
   '''simple docstring'''


   __lowercase			=		get_apod_data(UpperCamelCase_)
   __lowercase			=		apod_data["url"]
   __lowercase			=		img_url.split("/")[-1]
   __lowercase			=		requests.get(UpperCamelCase_,    stream=UpperCamelCase_)

   with open(F"""{path}/{img_name}""",    "wb+") as img_file:
      shutil.copyfileobj(response.raw,    UpperCamelCase_)
   del response
   return apod_data




def 						_A						(						UpperCamelCase_  : str)			->		dict:
   '''simple docstring'''


   __lowercase			=		"https://images-api.nasa.gov/search"
   return requests.get(UpperCamelCase_,    params={"q": query}).json()


if __name__ == "__main__":
   print(save_apod('YOUR API KEY'))
   _a				   =							get_archive_data('apollo 2011')['collection']['items']
   print(apollo_aaaa_items[0]['data'][0]['description'])




