[Feature] Enabled un-seen clients case to check the participation generalization gap #100
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…upload/download bytes, convergence rounds and time
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Jul 13, 2022
federatedscope/core/fed_runner.py
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| self.server = self._setup_server() | ||
| self.server.unseen_clients_id = unseen_clients_id |
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IMO, we have better not modify the attributes of server/client in fed_runner
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moved it into the setup_server() as sub action of init
federatedscope/core/fed_runner.py
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| @@ -102,6 +115,8 @@ def _setup_for_standalone(self): | |||
| for client_id in range(1, self.cfg.federate.client_num + 1): | |||
| self.client[client_id] = self._setup_client( | |||
| client_id=client_id, client_model=self._shared_client_model) | |||
| if client_id in unseen_clients_id: | |||
| self.client[client_id].is_unseen_client = True | |||
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moved it into the setup_server() as sub action of init
federatedscope/core/sampler.py
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| self.client_state[indices] = 1 | ||
| elif state == 'working': | ||
| self.client_state[indices] = 0 | ||
| if not isinstance(indices, list): |
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Shall we cover np.array here?
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modified accordingly, besides, we used another state named "unseen"
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Enabled un-seen clients simulation, such that we can check the participation generalization gap, refer ICLR'22, What Do We Mean by Generalization in Federated Learning?
This PR is based on the another PR (enhanced monitor #90)