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我所理解的方案,模型参数合并的方法主要有: 1)在worker端更新响应的参数w后,push到server覆盖旧的参数w; 2)server接收的是delta w, 再更新参数w; 不清楚ps-lite是什么策略更新参数的? 在代码中没找到参数更新的代码。。。(可能是我没理解) @mli @tqchen
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push的是gradient的话会加到weight上
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请问ps-lite代码在哪里?还是说要自己实现? (只找到 kv_app.h中 KVServerDefaultHandle,store[key]+= req_data.vals[i];) 如果是将push的gradient直接加到weight上,那么这个gradient 应该是乘以步长之后的gradient吧? @szha
ps架构下,只能接受asgd的更新策略,实际上所有分布式机器学习梯度更新策略都是这样子。可以去看mxnet中DCASGD
对,默认的是直接加,本地应该要乘以步长
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我所理解的方案,模型参数合并的方法主要有:
1)在worker端更新响应的参数w后,push到server覆盖旧的参数w;
2)server接收的是delta w, 再更新参数w;
不清楚ps-lite是什么策略更新参数的?
在代码中没找到参数更新的代码。。。(可能是我没理解)
@mli @tqchen
The text was updated successfully, but these errors were encountered: