0a8e27413d721bf8d753e5e6061cc24f5bf6474f,train.py,,,#,917

Before Change

    data_loaders = get_data_loaders(data_root, speaker_id, test_shuffle=True)

    // Model
    model = build_model()
    print(model)
    if use_cuda:
        model = model.cuda()

    receptive_field = model.receptive_field
    print("Receptive field (samples / ms): {} / {}".format(
        receptive_field, receptive_field / fs * 1000))

    optimizer = optim.Adam(model.parameters(),
                           lr=hparams.initial_learning_rate, betas=(
        hparams.adam_beta1, hparams.adam_beta2),
        eps=hparams.adam_eps, weight_decay=hparams.weight_decay)

After Change

    // Dataloader setup
    data_loaders = get_data_loaders(data_root, speaker_id, test_shuffle=True)

    device = torch.device("cuda" if use_cuda else "cpu")

    // Model
    model = build_model().to(device)

    receptive_field = model.receptive_field
    print("Receptive field (samples / ms): {} / {}".format(
        receptive_field, receptive_field / fs * 1000))

    optimizer = optim.Adam(model.parameters(),
                           lr=hparams.initial_learning_rate, betas=(
        hparams.adam_beta1, hparams.adam_beta2),
        eps=hparams.adam_eps, weight_decay=hparams.weight_decay,

Instances