Exemplos de __getattribute__ em Python

Exemplo n.º 1

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)

Exemplo n.º 2

Arquivo: __init__.py Projeto: yuv4r4j/kaggle-rfcx

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"])

Exemplo n.º 3

Arquivo: configuration.py Projeto: yuv4r4j/kaggle-birdcall-resnet-baseline-training

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"])