src/transformers/models/gpt2/convert_gpt2_original_tf_checkpoint_to_pytorch.py/convert_gpt2_checkpoint_to_pytorch
def convert_gpt2_checkpoint_to_pytorch(gpt2_checkpoint_path, gpt2_config_file, pytorch_dump_folder_path):
    # Construct model
    if gpt2_config_file == "":
        config = GPT2Config()
    else:
        config = GPT2Config.from_json_file(gpt2_config_file)
    model = GPT2Model(config)

    # Load weights from numpy
    load_tf_weights_in_gpt2(model, config, gpt2_checkpoint_path)

    # Save pytorch-model
    pytorch_weights_dump_path = pytorch_dump_folder_path + "/" + WEIGHTS_NAME
    pytorch_config_dump_path = pytorch_dump_folder_path + "/" + CONFIG_NAME
    print(f"Save PyTorch model to {pytorch_weights_dump_path}")
    torch.save(model.state_dict(), pytorch_weights_dump_path)
    print(f"Save configuration file to {pytorch_config_dump_path}")
    with open(pytorch_config_dump_path, "w", encoding="utf-8") as f:
        f.write(config.to_json_string())