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| """Import optimizer class dynamically.""" | |
| import argparse | |
| from espnet.utils.dynamic_import import dynamic_import | |
| from espnet.utils.fill_missing_args import fill_missing_args | |
| class OptimizerFactoryInterface: | |
| """Optimizer adaptor.""" | |
| def from_args(target, args: argparse.Namespace): | |
| """Initialize optimizer from argparse Namespace. | |
| Args: | |
| target: for pytorch `model.parameters()`, | |
| for chainer `model` | |
| args (argparse.Namespace): parsed command-line args | |
| """ | |
| raise NotImplementedError() | |
| def add_arguments(parser: argparse.ArgumentParser) -> argparse.ArgumentParser: | |
| """Register args.""" | |
| return parser | |
| def build(cls, target, **kwargs): | |
| """Initialize optimizer with python-level args. | |
| Args: | |
| target: for pytorch `model.parameters()`, | |
| for chainer `model` | |
| Returns: | |
| new Optimizer | |
| """ | |
| args = argparse.Namespace(**kwargs) | |
| args = fill_missing_args(args, cls.add_arguments) | |
| return cls.from_args(target, args) | |
| def dynamic_import_optimizer(name: str, backend: str) -> OptimizerFactoryInterface: | |
| """Import optimizer class dynamically. | |
| Args: | |
| name (str): alias name or dynamic import syntax `module:class` | |
| backend (str): backend name e.g., chainer or pytorch | |
| Returns: | |
| OptimizerFactoryInterface or FunctionalOptimizerAdaptor | |
| """ | |
| if backend == "pytorch": | |
| from espnet.optimizer.pytorch import OPTIMIZER_FACTORY_DICT | |
| return OPTIMIZER_FACTORY_DICT[name] | |
| elif backend == "chainer": | |
| from espnet.optimizer.chainer import OPTIMIZER_FACTORY_DICT | |
| return OPTIMIZER_FACTORY_DICT[name] | |
| else: | |
| raise NotImplementedError(f"unsupported backend: {backend}") | |
| factory_class = dynamic_import(name) | |
| assert issubclass(factory_class, OptimizerFactoryInterface) | |
| return factory_class | |