



"""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_( lowercase_  :				List[str]    , lowercase_  :				Tuple    , lowercase_  :				Optional[int]				)						->							List[str]:
				_lowerCamelCase   	=					TaConfig.from_json_file(__a				)
				print(F"""Building PyTorch model from configuration: {config}"""				)
				_lowerCamelCase   	=					TaForConditionalGeneration(__a				)

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

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


if __name__ == "__main__":
			__SCREAMING_SNAKE_CASE	:    int     				=   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.'''
			)
			__SCREAMING_SNAKE_CASE	:    Optional[Any]     				=   parser.parse_args()
			convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)




'''simple docstring'''
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificationProcessor
from .xnli import xnli_output_modes, xnli_processors, xnli_tasks_num_labels