"add part of trainer design doc" #2363
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helinwang reviewed Jun 2, 2017
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| ## Synchronize SGD | ||
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| In synchronize SGD, trainer need to wait other nodes finish training in every minibatch. And don't go on next epoch training if there is any node lag behind. |
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Here are some terms we usually use:
- step: one forward backward step, computes gradient.
- mini-batch: several data instances used in a single step.
- task: multiple mini-batches, the master server assigns task to trainers.
- pass: all training data, consisted of multiple tasks.
- epoch: start of a new pass.
In this line, "epoch" is used with "mini-batch", I think by "epoch" you actually mean "step"?
helinwang reviewed Jun 2, 2017
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| <img src="src/paddle-trainer.png" width="600"/> | ||
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| To wait other trainer in same epoch, use the waitEpochFinish to decide if an epoch has finished and enter next training epoch. |
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The trainer does not need to know about epoch (start of a new pass), it just get task from the master. So I think waitEpochFinish is not necessary.
helinwang reviewed Jun 2, 2017
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| ## Event Handler | ||
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| To select the trainer for process Python client event, same way as initialization parameters. Every trainer will try to get a distribute lock, then election a leader one. Leader trainer will keep to writing a file/ send metric data to evaluatorServer. Then python client can use that data draw metrics in real time. |
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Maybe "Event Handler" section is too early to be put into a design doc (we have not reached consensus yet).
Please see: #2364 (comment)
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