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| # Copyright (c) OpenMMLab. All rights reserved. | |
| import copy | |
| import inspect | |
| import torch | |
| from ...utils import Registry, build_from_cfg | |
| OPTIMIZERS = Registry('optimizer') | |
| OPTIMIZER_BUILDERS = Registry('optimizer builder') | |
| def register_torch_optimizers(): | |
| torch_optimizers = [] | |
| for module_name in dir(torch.optim): | |
| if module_name.startswith('__'): | |
| continue | |
| _optim = getattr(torch.optim, module_name) | |
| if inspect.isclass(_optim) and issubclass(_optim, | |
| torch.optim.Optimizer): | |
| OPTIMIZERS.register_module()(_optim) | |
| torch_optimizers.append(module_name) | |
| return torch_optimizers | |
| TORCH_OPTIMIZERS = register_torch_optimizers() | |
| def build_optimizer_constructor(cfg): | |
| return build_from_cfg(cfg, OPTIMIZER_BUILDERS) | |
| def build_optimizer(model, cfg): | |
| optimizer_cfg = copy.deepcopy(cfg) | |
| constructor_type = optimizer_cfg.pop('constructor', | |
| 'DefaultOptimizerConstructor') | |
| paramwise_cfg = optimizer_cfg.pop('paramwise_cfg', None) | |
| optim_constructor = build_optimizer_constructor( | |
| dict( | |
| type=constructor_type, | |
| optimizer_cfg=optimizer_cfg, | |
| paramwise_cfg=paramwise_cfg)) | |
| optimizer = optim_constructor(model) | |
| return optimizer | |