FATE icon indicating copy to clipboard operation
FATE copied to clipboard

An Industrial Grade Federated Learning Framework

Results 385 FATE issues
Sort by recently updated
recently updated
newest added
trafficstars

我使用数据集进行横向分箱,设置如下,分别设置了连续列,离散列和转换列: ![image](https://github.com/FederatedAI/FATE/assets/33820976/0891ab5a-b0c1-4fe2-aa23-91d004511415) 但是会报以下异常: ``` ==== detail start, at 20231219.235952.337 ==== Traceback (most recent call last): File "/data/projects/fate/eggroll/python/eggroll/core/utils.py", line 187, in wrapper return func(*args, **kw) File "/data/projects/fate/eggroll/python/eggroll/roll_pair/egg_pair.py", line 265, in run_task...

Signed-off-by: circlekkk Fixes ISSUE #xxx Changes: 1.add file: - python/federatedml/secureprotol/ecc/sm2.py 2.add SM2 parameters to the following file: - python/fate_client/pipeline/param/consts.py - python/federatedml/param/intersect_param.py - python/federatedml/util/consts.py 3.The following file code has been slightly...

fate-flow注册到zookeeper时服务地址乱码, ![图片](https://user-images.githubusercontent.com/93366859/202995660-7af1997c-40fe-4ef0-bbcd-5d2d7ef0e6a2.png) 例如 172.16.111.11:9360 再zookeeper中变成了172.16.111.11%3A9360

![4288bb16d6d6a8f09a3e2af746c091f](https://github.com/FederatedAI/FATE/assets/114332210/8ed2d61c-2ce7-48f2-8311-ce2822f11549) ![4288bb16d6d6a8f09a3e2af746c091f](https://github.com/FederatedAI/FATE/assets/114332210/e0b5d031-ff19-4212-ba25-2ae15bed7f54) fateflow 注册失效

![image](https://github.com/FederatedAI/FATE/assets/93757135/40545f47-8afb-45b5-812f-068301e44385)

在项目中遇到一个问题,需要设置某些特征为单调约束,在XGBoost中可以通过设置参数“monotone_constraint”来实现(如下图),但在SecureBoost中始终未找到相关的设置。 ![WXWorkCapture_16988264397780](https://github.com/FederatedAI/FATE/assets/17230130/3a8ce107-30cc-46b2-bacd-87d695609293)

feature-request

**Describe the bug** Hetero-nn does not calculate the validation loss. It only runs the validation set during eval. **To Reproduce** Run Hetero-nn with a validation set. **Expected behavior** A graph...

我使用pipeline构建神经网络,横向联邦学习任务。 自定义模型和数据问题解决,使用pipeline构建任务,可以运行pipeline.fit开始训练,可以看见日志显示任务训练了设定的epoch,但是训练完毕后报错socket.timeout,我猜测是run_ip显示为'run_ip': 'xxx.xxx.xxx.xxx'导致。 日志显示的参数如下 {'job_id': '202311290103155381610', 'component_name': 'reader_0', 'task_id': '202311290103155381610_reader_0', 'task_version': '0', 'role': 'guest', 'party_id': '9999', 'run_ip': 'xxx.xxx.xxx.xxx', 'run_pid': 467154, 'run_port': '9380', 'party_status': 'running'}

**Is your feature request related to a problem? Please describe.** A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] **Describe the solution you'd...