Exemplos de get_default_optimizer_params em Python

Exemplo n.º 1

Arquivo: train_net.py Projeto: caodoanh2001/Traffic_sign_detection

    def build_optimizer(cls, cfg, model):
        """
        Build an optimizer from config.
        """
        params = get_default_optimizer_params(
            model,
            base_lr=cfg.SOLVER.BASE_LR,
            weight_decay=cfg.SOLVER.WEIGHT_DECAY,
            weight_decay_norm=cfg.SOLVER.WEIGHT_DECAY_NORM,
            bias_lr_factor=cfg.SOLVER.BIAS_LR_FACTOR,
            weight_decay_bias=cfg.SOLVER.WEIGHT_DECAY_BIAS,
        )

        optimizer_type = cfg.SOLVER.OPTIMIZER
        if optimizer_type == "SGD":
            return maybe_add_gradient_clipping(cfg, torch.optim.SGD)(
                params,
                cfg.SOLVER.BASE_LR,
                momentum=cfg.SOLVER.MOMENTUM,
                nesterov=cfg.SOLVER.NESTEROV,
            )
        elif optimizer_type == "ADAM":
            return maybe_add_gradient_clipping(cfg, torch.optim.Adam)(
                params, cfg.SOLVER.BASE_LR)
        else:
            raise NotImplementedError(f"no optimizer type {optimizer_type}")

Exemplo n.º 2

Arquivo: train_net_adam.py Projeto: mhbkb/cs231N-project

    def build_optimizer(cls, cfg, model):
        """
        Build an optimizer from config.
        """
        params = get_default_optimizer_params(
            model,
            weight_decay=cfg.SOLVER.WEIGHT_DECAY,
            weight_decay_norm=cfg.SOLVER.WEIGHT_DECAY_NORM,
        )

        return maybe_add_gradient_clipping(cfg, torch.optim.Adam)(
            params, cfg.SOLVER.BASE_LR)