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初始化服务器模型的时候使用了self.global_model = models.get_model(self.conf["model_name"]) 但是在添加参与客户端的时候,为什么也是使用self.local_model = models.get_model(self.conf["model_name"]) 初始化函数参数里的model没有被使用,我觉得应该改为self.local_model=model, local_train函数不需要model参数,在前面每个通讯选中参与者时将参与者的self.model设置成新的全局模型会不会好一点。
self.global_model = models.get_model(self.conf["model_name"])
self.local_model = models.get_model(self.conf["model_name"])
self.local_model=model
local_train
model
The text was updated successfully, but these errors were encountered:
哈咯,请问lambda什么含义呀?为什么取0.1?随机选五人训练聚合,不应该取0.2吗
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取0.2就是之后的全局模型完全取决于本轮次客户端提交的参数差,如果提交小于0.2那就代表还考虑了全局模型的权重
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初始化服务器模型的时候使用了
self.global_model = models.get_model(self.conf["model_name"])
但是在添加参与客户端的时候,为什么也是使用
self.local_model = models.get_model(self.conf["model_name"])
初始化函数参数里的model没有被使用,我觉得应该改为
self.local_model=model
,local_train
函数不需要model
参数,在前面每个通讯选中参与者时将参与者的self.model设置成新的全局模型会不会好一点。The text was updated successfully, but these errors were encountered: