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https://issues.apache.org/jira/browse/SYSTEMML-2299?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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LI Guobao updated SYSTEMML-2299:
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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 of 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 struct format. (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, 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 struct format.)
> 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 of 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 struct format.
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