def get_optimizer(model: nn.Module): optimizer_name = CFG.optimizer_name if optimizer_name == "SAM": base_optimizer_name = CFG.base_optimizer if __OPTIMIZERS__.get(base_optimizer_name) is not None: base_optimizer = __OPTIMIZERS__[base_optimizer_name] else: base_optimizer = optim.__getattribute__(base_optimizer_name) return SAM(model.parameters(), base_optimizer, **CFG.optimizer_params) if __OPTIMIZERS__.get(optimizer_name) is not None: return __OPTIMIZERS__[optimizer_name](model.parameters(), **CFG.optimizer_params) else: return optim.__getattribute__(optimizer_name)(model.parameters(), **CFG.optimizer_params)
def get_optimizer(model: nn.Module, config: dict): optimizer_config = config["optimizer"] optimizer_name = optimizer_config.get("name") if optimizer_name == "SAM": base_optimizer_name = optimizer_config.get("base_optimizer") if __OPTIMIZERS__.get(base_optimizer_name) is not None: base_optimizer = __OPTIMIZERS__[base_optimizer_name] else: base_optimizer = optim.__getattribute__(base_optimizer_name) return SAM(model.parameters(), base_optimizer, **optimizer_config["params"]) if __OPTIMIZERS__.get(optimizer_name) is not None: return __OPTIMIZERS__[optimizer_name](model.parameters(), **optimizer_config["params"]) else: return optim.__getattribute__(optimizer_name)( model.parameters(), **optimizer_config["params"])
def get_optimizer(model: nn.Module, config: dict): optimizer_config = config["optimizer"] optimizer_name = optimizer_config.get("name") return optim.__getattribute__(optimizer_name)(model.parameters(), **optimizer_config["params"])