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Source code for mmaction.engine.optimizers.swin_optim_wrapper_constructor

# Copyright (c) OpenMMLab. All rights reserved.
from functools import reduce
from operator import mul
from typing import List

import torch.nn as nn
from mmengine.logging import print_log
from mmengine.optim import DefaultOptimWrapperConstructor

from mmaction.registry import OPTIM_WRAPPER_CONSTRUCTORS


[docs]@OPTIM_WRAPPER_CONSTRUCTORS.register_module() class SwinOptimWrapperConstructor(DefaultOptimWrapperConstructor):
[docs] def add_params(self, params: List[dict], module: nn.Module, prefix: str = 'base', **kwargs) -> None: """Add all parameters of module to the params list. The parameters of the given module will be added to the list of param groups, with specific rules defined by paramwise_cfg. Args: params (list[dict]): A list of param groups, it will be modified in place. module (nn.Module): The module to be added. prefix (str): The prefix of the module. Defaults to ``'base'``. """ for name, param in module.named_parameters(recurse=False): param_group = {'params': [param]} if not param.requires_grad: params.append(param_group) continue param_group['lr'] = self.base_lr if self.base_wd is not None: param_group['weight_decay'] = self.base_wd processing_keys = [ key for key in self.paramwise_cfg if key in f'{prefix}.{name}' ] if processing_keys: param_group['lr'] *= \ reduce(mul, [self.paramwise_cfg[key].get('lr_mult', 1.) for key in processing_keys]) if self.base_wd is not None: param_group['weight_decay'] *= \ reduce(mul, [self.paramwise_cfg[key]. get('decay_mult', 1.) for key in processing_keys]) params.append(param_group) for key, value in param_group.items(): if key == 'params': continue full_name = f'{prefix}.{name}' if prefix else name print_log( f'paramwise_options -- ' f'{full_name}: {key} = {round(value, 8)}', logger='current') for child_name, child_mod in module.named_children(): child_prefix = f'{prefix}.{child_name}' if prefix else child_name self.add_params(params, child_mod, prefix=child_prefix)
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