Comments (9)
您好,请问可以给出执行的具体命令吗
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您好,请问可以给出执行的具体命令吗
python generate_data.py -d mnist -cn 1000 -a 0.1
from fl-bench.
您好,请问可以给出执行的具体命令吗
python generate_data.py -d mnist -cn 1000 -a 0.1
然后我一步一步去print()我发现在打印min_size的时候出现这种
from fl-bench.
可以尝试把 --least_sample
调低一点(默认为 40),或者把 -a
调高一点。
使用 dirichlet 切分数据时,当 -a
很小(比如 0.1)而客户端数量过多时,很容易发生这种死循环出不来的情况,这并不是代码的问题。
from fl-bench.
可以尝试把 调低一点(默认为 40),或者把 调高一点。 使用 dirichlet 切分数据时,当 很小(比如 0.1)而客户端数量过多时,很容易发生这种死循环出不来的情况,这并不是代码的问题。
--least_sample``-a``-a
那如果当我想设置更大的客户端数量时候,-a我设置多少才最合适,-a的上限是什么呀,多少的时候代表没有异构的性质,因为我记得您说过,它越小异构性越强。
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-a 的设置是看您的个人要求的。-a 需要大于 0, -a 越接近 0,切分出来的数据集越不均匀。 如果你想切分数据时不引入异构性,你可以使用 python generate_data.py --iid 1
来均匀切分数据集。
from fl-bench.
-a 的设置是看您的个人要求的。-a 需要大于 0, -a 越接近 0,切分出来的数据集越不均匀。 如果你想切分数据时不引入异构性,你可以使用
python generate_data.py --iid 1
来均匀切分数据集。
我是想要异构的
from fl-bench.
异构也有程度大小之分。至于你想要怎样的异构,还请自己斟酌,你可以多跑几次代码,通过查看生成的 data/${dataset}/all_stats.json
来观察数据的分布情况来判断。我这边给不了什么建议。
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好的,非常感谢您的回答
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Related Issues (20)
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