


'''simple docstring'''





import argparse

from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging


logging.set_verbosity_info()







def        lowerCAmelCase_  (      __lowerCamelCase							,			__lowerCamelCase							,			__lowerCamelCase			):
							# Initialise PyTorch model
							__snake_case	:    Optional[Any]											=     TaConfig.from_json_file(__lowerCamelCase			)
							print(F'Building PyTorch model from configuration: {config}'			)
							__snake_case	:    Dict											=     TaForConditionalGeneration(__lowerCamelCase			)

							# Load weights from tf checkpoint
							load_tf_weights_in_ta(__lowerCamelCase							,			__lowerCamelCase							,			__lowerCamelCase			)

							# Save pytorch-model
							print(F'Save PyTorch model to {pytorch_dump_path}'			)
							model.save_pretrained(__lowerCamelCase			)


if __name__ == "__main__":
			_snake_case  :	Any			      =       argparse.ArgumentParser()
			# Required parameters
			parser.add_argument(
			    "--tf_checkpoint_path", default=None, type=str, required=True, help="Path to the TensorFlow checkpoint path."
			)
			parser.add_argument(
			    "--config_file",
			    default=None,
			    type=str,
			    required=True,
			    help=(
			        "The config json file corresponding to the pre-trained T5 model. \nThis specifies the model architecture."
			    ),
			)
			parser.add_argument(
			    "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
			)
			_snake_case  :	Any			      =       parser.parse_args()
			convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)





import warnings

from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor


_snake_case  :	List[str]			      =       logging.get_logger(__name__)

class        a	(_lowerCAmelCase   ):




							"""simple docstring"""


							def __init__(							self :						int					,			*lowerCamelCase :						Any					,			**lowerCamelCase :						Union[str, Any]       )			->					None:
														warnings.warn(
														    "The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
														    " Please use PoolFormerImageProcessor instead."					,			lowerCamelCase					,			)
														super().__init__(*lowerCamelCase					,			**lowerCamelCase       )

