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FedGraphnn -- wandb utilization #2025
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Hello @pleonidou thank you for reaching out. You can store any custom results you need either at the aggregator or the client side, by extending the following functions: The test_all() function in the aggregator is executed at the end of every federation round. The train() function at the client is executed at the beginning of the federation round and the test() function at the end of local training. For overriding the wandb functionality you can refer to this line here: https://github.com/FedML-AI/FedML/blob/master/python/examples/federate/prebuilt_jobs/fedgraphnn/ego_networks_node_clf/trainer/federated_nc_aggregator.py#L43 In general, you can also use the fedml.log() functionality to record your custom metrics, but by extending the functionality as described above in both the aggregator and the client class you have more control on what is being recorded. |
Many thanks for the swift response!
…On Tue, Apr 9, 2024 at 6:55 AM Dimitris Stripelis ***@***.***> wrote:
Hello @pleonidou <https://github.com/pleonidou> thank you for reaching
out. You can store any custom results you need either at the aggregator or
the client side, by extending the following functions:
Aggregator:
https://github.com/FedML-AI/FedML/blob/master/python/examples/federate/prebuilt_jobs/fedgraphnn/ego_networks_node_clf/trainer/federated_nc_aggregator.py#L25
The test_all() function in the aggregator is executed at the end of every
federation round.
Client:
https://github.com/FedML-AI/FedML/blob/master/python/examples/federate/prebuilt_jobs/fedgraphnn/ego_networks_node_clf/trainer/federated_nc_trainer.py#L22
The train() function at the client is executed at the beginning of the
federation round and the test() function at the end of local training.
For overriding the wandb functionality you can refer to this line here:
https://github.com/FedML-AI/FedML/blob/master/python/examples/federate/prebuilt_jobs/fedgraphnn/ego_networks_node_clf/trainer/federated_nc_aggregator.py#L43
In general, you can also use the fedml.log() functionality to record your
custom metrics, but by extending the functionality as described above in
both the aggregator and the client class you have more control on what is
being recorded.
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Hi, I would like to ask if there is an option to use the fedgraphnn examples with ego networks for node classification without the wandb?
I would like to store the results per client and server aggregation locally.
I am referring to this example: https://github.com/FedML-AI/FedML/tree/master/python/examples/federate/prebuilt_jobs/fedgraphnn/ego_networks_node_clf
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