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From "LI Guobao (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SYSTEMML-2299) API design of the paramserv function
Date Wed, 09 May 2018 08:44:00 GMT

     [ https://issues.apache.org/jira/browse/SYSTEMML-2299?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

LI Guobao updated SYSTEMML-2299:
--------------------------------
    Description: The objective of “paramserv” built-in function is to update an initial
or existing model with configuration. An initial function signature would be _model'=paramserv(model,
X, y, X_val, y_val, upd=fun1, mode=SYNC, freq=EPOCH, agg=fun2, epochs=100, batchsize=64, k=7,
checkpointing=rollback)_. We are interested in providing the model (which will be a struct-like
data structure consisting the weights, the biases and the hyperparameters), the training features
and labels, the validation features and labels, the batch update function, the update strategy
(e.g. sync, async, hogwild!, stale-synchronous), the update frequency (e.g. epoch or mini-batch),
the gradient aggregation function, the number of epoch, the batch size, the degree of parallelism
as well as the checkpointing strategy (e.g. rollback recovery). And the function will return
a trained model in format of struct.  (was: The objective of “paramserv” built-in function
is to update an initial or existing model with configuration. An initial function signature
would be _model'=paramserv(model, X, y, X_val, y_val, g_cal_fun, upd=fun1, mode=SYNC, freq=EPOCH,
agg=fun2, epochs=100, batchsize=64, k=7, checkpointing=rollback)_. We are interested in providing
the model, the training features and labels, the validation features and labels, the gradient
calculation function, the batch update function, the update strategy (e.g. sync, async, hogwild!,
stale-synchronous), the update frequency (e.g. epoch or batch), the aggregation function,
the number of epoch, the batch size, the degree of parallelism as well as the checkpointing
strategy (e.g. rollback recovery).)

> API design of the paramserv function
> ------------------------------------
>
>                 Key: SYSTEMML-2299
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-2299
>             Project: SystemML
>          Issue Type: Sub-task
>            Reporter: LI Guobao
>            Assignee: LI Guobao
>            Priority: Major
>
> The objective of “paramserv” built-in function is to update an initial or existing
model with configuration. An initial function signature would be _model'=paramserv(model,
X, y, X_val, y_val, upd=fun1, mode=SYNC, freq=EPOCH, agg=fun2, epochs=100, batchsize=64, k=7,
checkpointing=rollback)_. We are interested in providing the model (which will be a struct-like
data structure consisting the weights, the biases and the hyperparameters), the training features
and labels, the validation features and labels, the batch update function, the update strategy
(e.g. sync, async, hogwild!, stale-synchronous), the update frequency (e.g. epoch or mini-batch),
the gradient aggregation function, the number of epoch, the batch size, the degree of parallelism
as well as the checkpointing strategy (e.g. rollback recovery). And the function will return
a trained model in format of struct.



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