





"""simple docstring"""
import argparse

from transformers import ConvBertConfig, ConvBertModel, TFConvBertModel, load_tf_weights_in_convbert
from transformers.utils import logging


logging.set_verbosity_info()

def 		_SCREAMING_SNAKE_CASE (_UpperCAmelCase				:						int     ,    _UpperCAmelCase				:						Tuple     ,    _UpperCAmelCase				:						Union[str, Any] ):
 lowerCAmelCase													=   ConvBertConfig.from_json_file(_UpperCAmelCase )
 lowerCAmelCase													=   ConvBertModel(_UpperCAmelCase )

 lowerCAmelCase													=   load_tf_weights_in_convbert(_UpperCAmelCase     ,    _UpperCAmelCase     ,    _UpperCAmelCase )
 model.save_pretrained(_UpperCAmelCase )

 lowerCAmelCase													=   TFConvBertModel.from_pretrained(_UpperCAmelCase     ,    from_pt=_UpperCAmelCase )
 tf_model.save_pretrained(_UpperCAmelCase )


if __name__ == "__main__":
    __UpperCamelCase    :	Tuple						=     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(
        '''--convbert_config_file''',
        default=None,
        type=str,
        required=True,
        help=(
            '''The config json file corresponding to the pre-trained ConvBERT model. \n'''
            '''This specifies the model architecture.'''
        ),
    )
    parser.add_argument(
        '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
    )
    __UpperCamelCase    :	str						=     parser.parse_args()
    convert_orig_tfa_checkpoint_to_pytorch(args.tf_checkpoint_path, args.convbert_config_file, args.pytorch_dump_path)












"""simple docstring"""
def 		_SCREAMING_SNAKE_CASE (_UpperCAmelCase				:						int     ,    _UpperCAmelCase				:						int ):
 return (input_a, input_a).count(0 ) % 2

def 		_SCREAMING_SNAKE_CASE ():
 assert xor_gate(0     ,    0 ) == 0
 assert xor_gate(0     ,    1 ) == 1
 assert xor_gate(1     ,    0 ) == 1
 assert xor_gate(1     ,    1 ) == 0


if __name__ == "__main__":
       print(xor_gate(0, 0))
       print(xor_gate(0, 1))





