rework the code to not use the walrus operator because colab's 3.7 does not support it

    weights = hypernetwork.weights()

    for weight in weights:

        weight.requires_grad = True

    # Here we use optimizer from saved HN, or we can specify as UI option.

    if (optimizer_name := hypernetwork.optimizer_name) in optimizer_dict:

    if hypernetwork.optimizer_name in optimizer_dict:

        optimizer = optimizer_dict[hypernetwork.optimizer_name](params=weights, lr=scheduler.learn_rate)

        optimizer_name = hypernetwork.optimizer_name

    else:

        print(f"Optimizer type {optimizer_name} is not defined!")

        print(f"Optimizer type {hypernetwork.optimizer_name} is not defined!")

        optimizer = torch.optim.AdamW(params=weights, lr=scheduler.learn_rate)

        optimizer_name = 'AdamW'

    if hypernetwork.optimizer_state_dict:  # This line must be changed if Optimizer type can be different from saved optimizer.

        try:

            optimizer.load_state_dict(hypernetwork.optimizer_state_dict)