codingutf8 2021 the huggingface inc team licensed under the apache license version 2 0 the license you may not use this file except in compliance with the license you may obtain a copy of the license at http www apache orglicenseslicense2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license convert bigbird checkpoint import argparse from transformers import bigbirdconfig bigbirdforpretraining bigbirdforquestionanswering loadtfweightsinbigbird from transformers utils import logging logging setverbosityinfo def converttfcheckpointtopytorchtfcheckpointpath bigbirdconfigfile pytorchdumppath istriviaqa initialise pytorch model config bigbirdconfig fromjsonfilebigbirdconfigfile printfbuilding pytorch model from configuration config if istriviaqa model bigbirdforquestionansweringconfig else model bigbirdforpretrainingconfig load weights from tf checkpoint loadtfweightsinbigbirdmodel tfcheckpointpath istriviaqaistriviaqa save pytorchmodel printfsave pytorch model to pytorchdumppath model savepretrainedpytorchdumppath if name main parser argparse argumentparser required parameters parser addargument tfcheckpointpath defaultnone typestr requiredtrue helppath to the tensorflow checkpoint path parser addargument bigbirdconfigfile defaultnone typestr requiredtrue help the config json file corresponding to the pretrained bert model n this specifies the model architecture parser addargument pytorchdumppath defaultnone typestr requiredtrue helppath to the output pytorch model parser addargument istriviaqa actionstoretrue helpwhether to convert a model with a triviaqa head args parser parseargs converttfcheckpointtopytorch args tfcheckpointpath args bigbirdconfigfile args pytorchdumppath args istriviaqa coding utf 8 2021 the huggingface inc team licensed under the apache license version 2 0 the license you may not use this file except in compliance with the license you may obtain a copy of the license at http www apache org licenses license 2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license convert bigbird checkpoint initialise pytorch model load weights from tf checkpoint save pytorch model required parameters
import argparse

from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging


logging.set_verbosity_info()


def convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, big_bird_config_file, pytorch_dump_path, is_trivia_qa):
    
    config = BigBirdConfig.from_json_file(big_bird_config_file)
    print(f"Building PyTorch model from configuration: {config}")

    if is_trivia_qa:
        model = BigBirdForQuestionAnswering(config)
    else:
        model = BigBirdForPreTraining(config)

    
    load_tf_weights_in_big_bird(model, tf_checkpoint_path, is_trivia_qa=is_trivia_qa)

    
    print(f"Save PyTorch model to {pytorch_dump_path}")
    model.save_pretrained(pytorch_dump_path)


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    
    parser.add_argument(
        "--tf_checkpoint_path", default=None, type=str, required=True, help="Path to the TensorFlow checkpoint path."
    )
    parser.add_argument(
        "--big_bird_config_file",
        default=None,
        type=str,
        required=True,
        help=(
            "The config json file corresponding to the pre-trained BERT 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."
    )
    parser.add_argument(
        "--is_trivia_qa", action="store_true", help="Whether to convert a model with a trivia_qa head."
    )
    args = parser.parse_args()
    convert_tf_checkpoint_to_pytorch(
        args.tf_checkpoint_path, args.big_bird_config_file, args.pytorch_dump_path, args.is_trivia_qa
    )