Cannot load pretrained model when using DDP about speechbrain HOT 4 OPEN

    # This flag enables the inbuilt cudnn auto-tuner
    torch.backends.cudnn.benchmark = True

    # CLI:
    hparams_file, run_opts, overrides = sb.parse_arguments(sys.argv[1:])

    # Initialize ddp (useful only for multi-GPU DDP training)
    sb.utils.distributed.ddp_init_group(run_opts)

    # Load hyperparameters file with command-line overrides
    with open(hparams_file) as fin:
        hparams = load_hyperpyyaml(fin, overrides)


    sb.core.create_experiment_directory(
        experiment_directory=hparams["output_folder"],
        hyperparams_to_save=hparams_file,
        overrides=overrides,
    )
    # Initialization of the pre-trainer
    run_on_main(hparams["pretrainer"].collect_files)
    hparams["pretrainer"].load_collected(device=run_opts["device"])
    # run_on_main(hparams["pretrainer"].load_collected(device=run_opts["device"]))

    #print(hparams["pretrainer"].loadables["embedding_model"] is hparams['embedding_model'] )


    # Brain class initialization
    speaker_brain = SpeakerBrain(
        modules=hparams["modules"],
        opt_class=hparams["opt_class"],
        hparams=hparams,
        run_opts=run_opts,
        checkpointer=hparams["checkpointer"],
    )
    #speaker_brain.optimizer.add_param_group({'params':speaker_brain.modules.embedding_model.parameters(),'lr':1e-4})
    #speaker_brain.modules.embedding_model = hparams["pretrainer"].loadables["embedding_model"]

    #print(speaker_brain.modules.embedding_model.state_dict())


    # Training
    speaker_brain.fit(
        speaker_brain.hparams.epoch_counter,
        train_data,
        valid_data,
        train_loader_kwargs=hparams["dataloader_options"],
        valid_loader_kwargs=hparams["dataloader_options"],
    )