FATE
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An Industrial Grade Federated Learning Framework
https://fate.readthedocs.io/en/v1.7.2/federatedml_component/sir/
我们将两个fate的数据库改为指定数据库之后,进行联邦学习任务报错。请问会是什么原因呢
(venv) [root@fate_216 logs]# pipeline init --ip 10.248.202.216 --port 9380 Pipeline configuration succeeded. (venv) [root@fate_216 logs]# flow test toy -gid 9999 -hid 9999 { "code": 13, "message": "Permission denied" } 本机IP:10.248.202.216
联邦建模时出错
 在进行联邦建模时运行到LR那一步报这个错误,看起来像是通信的问题,可以详细说一下出现这个问题的原因吗
看到升级说明里,2.1.1新增了 Support server model saving in Homo-NN ML aggregator support aggregation of torch.bfloat16 data type 2.2 Deployment Upgrade from Python 3.8 to Python 3.10 Upgrade the PyTorch version to 2.x...
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您好,开发者可以推荐一下fate部署的机器的配置吗?cpu和内存之类的。
单机部署好的fate,除了能访问前端的fateboard,还有其他方式能在前端访问吗,或者怎么找到一个可以返回训练结果的后端,从而实现前后端的互通。
Hi, I'm trying to implement ensemble xgboost model with 1D conv layer using FATE. (the model details in here: https://arxiv.org/pdf/2304.07537) To do this, i train xgboost in my custom fate...