src/transformers/models/openai/convert_openai_original_tf_checkpoint_to_pytorch.py/convert_openai_checkpoint_to_pytorch
def convert_openai_checkpoint_to_pytorch(openai_checkpoint_folder_path, openai_config_file, pytorch_dump_folder_path):
    # Construct model
    if openai_config_file == "":
        config = OpenAIGPTConfig()
    else:
        config = OpenAIGPTConfig.from_json_file(openai_config_file)
    model = OpenAIGPTModel(config)

    # Load weights from numpy
    load_tf_weights_in_openai_gpt(model, config, openai_checkpoint_folder_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())