



import argparse

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


logging.set_verbosity_info()


def   lowercase_	(   lowerCAmelCase__	:  int			,							lowerCAmelCase__	:  Tuple ):

			"""simple docstring"""





			__UpperCAmelCase   :      Tuple										=     CanineConfig()
			__UpperCAmelCase   :      List[Any]										=     CanineModel(lowerCAmelCase__ )
			model.eval()

			print(f'Building PyTorch model from configuration: {config}' )

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

			# Save pytorch-model (weights and configuration)
			print(f'Save PyTorch model to {pytorch_dump_path}' )
			model.save_pretrained(lowerCAmelCase__ )

			# Save tokenizer files
			__UpperCAmelCase   :      Union[str, Any]										=     CanineTokenizer()
			print(f'Save tokenizer files to {pytorch_dump_path}' )
			tokenizer.save_pretrained(lowerCAmelCase__ )


if __name__ == "__main__":
					_UpperCamelCase											=			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.''',
					)
					_UpperCamelCase											=			parser.parse_args()
					convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)









'''simple docstring'''
import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


_UpperCamelCase											=			logging.get_logger(__name__)



class _A  (    __SCREAMING_SNAKE_CASE    ):





		def __init__(     self ,       *__UpperCAmelCase ,       **__UpperCAmelCase				)       ->     None:

					'''simple docstring'''
					warnings.warn(
					    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
					    """ Please use MobileNetV2ImageProcessor instead.""" ,       __UpperCAmelCase ,       )
					super().__init__(*__UpperCAmelCase ,       **__UpperCAmelCase				)




