Standard implementations of FedLab and its provided benchmarks.

Overview

FedLab-benchmarks

This repo contains standard implementations of FedLab and its provided benchmarks.

Currently, following algorithms or benchrmarks are available:

TODO:


We highly welcome you to contribute federated algorithm implemented by FedLab. If you encounter any problems, do not hesitate to submit an issue or send an email to the repo maintainer.

Comments
  • 运行fedasync/cross_process demo出错

    运行fedasync/cross_process demo出错

    在执行跨进程的异步FL任务时会陷入等待。

    hm@hm-IdeaCentre-GeekPro-15ICK:~/test/fedasync$ bash quick_start.sh 
    torch.distributed connection is initializing with ip address 127.0.0.1:3002, rank 0, world size: 3, backend gloo, ethernet None.
    torch.distributed connection is initializing with ip address 127.0.0.1:3002, rank 1, world size: 3, backend gloo, ethernet None.
    torch.distributed connection is initializing with ip address 127.0.0.1:3002, rank 2, world size: 3, backend gloo, ethernet None.
    2022-04-07 22:13:36,811 - root - INFO - Added key: store_based_barrier_key:1 to store for rank: 1
    2022-04-07 22:13:36,811 - root - INFO - Added key: store_based_barrier_key:1 to store for rank: 0
    2022-04-07 22:13:36,811 - root - INFO - Added key: store_based_barrier_key:1 to store for rank: 2
    2022-04-07 22:13:36,812 - client 1 - INFO - request parameter procedure
    2022-04-07 22:13:36,812 - client 2 - INFO - request parameter procedure
    
    opened by kid1999 6
  • [Fedasync] Executing error

    [Fedasync] Executing error

    I got this error when executing FedLab-benchmarks/fedlab_benchmarks/fedasync/standalone/standalone.py with fedlab==1.1.2.

    Traceback (most recent call last):
      File "standalone.py", line 300, in <module>
        params_list = trainer.train(model_parameters=model_parameters,
      File "/home/xuan/.local/lib/python3.8/site-packages/fedlab/core/client/scale/trainer.py", line 77, in train
        self._LOGGER.info(
    AttributeError: 'NoneType' object has no attribute 'info'
    

    Am I missing anything? Furthermore, which version of fedlab should I used in fedlab_benchmark?

    opened by ysrese 3
  • 异步多线程中 model_time 传输是否有问题?

    异步多线程中 model_time 传输是否有问题?

    server manager 传输的 torch.Tensor(self._handler.server_time) client 回传时直接使用self.model_time + 1 然后server再次拿到model_time进行聚合的时候,staleness = self.current_time - receive_model_time

    最后导致传输的model_time tensor持续变大! 2022-04-14 05:34:07,112 - server - INFO - model time : tensor([-1.1402e+13, 1.0000e+00, 1.0000e+00, 1.0000e+00]) 2022-04-14 05:34:07,112 - server - INFO - staleness : tensor([1.1402e+13, 4.0000e+00, 4.0000e+00, 4.0000e+00])

    opened by kid1999 3
  • Errors in the current version

    Errors in the current version

    When I try to run the demo, there seems that some files are lost, like the following ModuleNotFoundError: No module named 'leaf.read_util'.

    Moreover, It is suggested that your example on LEAF can be completed in a folder instead of using ''...'' other ways to call the files under the parent folder, it makes the program look messy and prone to the following errors: ValueError: attempted relative import beyond top-level package

    Anyway, this is a nice work for the federated learning experiment. I hope it can be improved.

    bug 
    opened by Zmjcc 3
  • Ask for help

    Ask for help

    Hello, Thanks for reading~

    I follow the tutorial from :https://github.com/SMILELab-FL/FedLab-benchmarks/blob/master/fedlab_benchmarks/datasets/fmnist/fmnist_tutorial.ipynb

    However, the following error exists: FileNotFoundError: [Errno 2] No such file or directory: '../partition-reports/fmnist_noniid-label_1_clients_10.csv'

    How can I fix it? Please.

    good first issue help wanted 
    opened by skyejy 3
  • 运行实例中的 demo 时出错

    运行实例中的 demo 时出错

    跟着 示例 走, 当运行 standalone.py 时报错

    Traceback (most recent call last):
      File "standalone.py", line 21, in <module>
        from models.cnn import CNN_MNIST
    ModuleNotFoundError: No module named 'models'
    
    
    opened by KarhouTam 2
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