Feature(wxh): Add FedAMP algo and fix bugs.#25
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XinghaoWu wants to merge 1 commit intoFLAIR-Community:mainfrom
Open
Feature(wxh): Add FedAMP algo and fix bugs.#25XinghaoWu wants to merge 1 commit intoFLAIR-Community:mainfrom
XinghaoWu wants to merge 1 commit intoFLAIR-Community:mainfrom
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XinghaoWu
commented
Oct 25, 2023
XinghaoWu
commented
- Add FedAMP algo.
- Add the FedCAC paper link in README.md.
- Remove the default momentum in default_config.py to fix the bug when setting the optimizer to Adam.
2. Add FedCAC paper link in README.md. 3. Remove the default momentum in default_config.py to fix the bug when set optmizer to adam.
kxzxvbk
changed the title
kxzxvbk
reviewed
Oct 26, 2023
| class FedAMPClient(BaseClient): | ||
| """ | ||
| Overview: | ||
| This class is the base implementation of client in 'Bold but Cautious: Unlocking the Potential of Personalized |
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Correct this document, not FedCAC.
kxzxvbk
reviewed
Oct 26, 2023
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| def __init__(self, args, client_id, train_dataset, test_dataset=None): | ||
| """ | ||
| Initializing train dataset, test dataset(for personalized settings). |
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Correct this document, the purpose is to get a copy of local model.
kxzxvbk
reviewed
Oct 26, 2023
| super(FedAMPClient, self).__init__(args, client_id, train_dataset, test_dataset) | ||
| self.client_u = copy.deepcopy(self.model) | ||
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| def FedAMP_Loss_client(self): |
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You can use the get_model_difference function (defined in fling/utils/torch_utils.py ) for simplification.
kxzxvbk
reviewed
Oct 26, 2023
| from fling.utils.utils import weight_flatten | ||
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| @CLIENT_REGISTRY.register('fedamp_client') | ||
| class FedAMPClient(BaseClient): |
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I'm wondering whether this client is identical to FedProxClient? What's the differences?
kxzxvbk
reviewed
Oct 26, 2023
| coef = torch.zeros(self.args.client.client_num) | ||
| for j, mw in enumerate(self.client_ws): | ||
| if i == j: continue | ||
| sub = weights[i] - weights[j] |
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Rewrite it using fling.utils.get_model_difference
kxzxvbk
reviewed
Oct 26, 2023
kxzxvbk
reviewed
Oct 26, 2023
| ) | ||
| return participated_clients | ||
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| def weight_flatten(model) -> torch.Tensor: |
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I suppose that this function can be removed.
Collaborator
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Reformat the code before final merge. |
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Add example configs for cifar100, mnist and tiny-imagenet. |
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