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From "Ngin Yun Chuan (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SINGA-412) Log visualization API
Date Fri, 07 Dec 2018 04:41:00 GMT

    [ https://issues.apache.org/jira/browse/SINGA-412?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16712331#comment-16712331
] 

Ngin Yun Chuan commented on SINGA-412:
--------------------------------------

Hi [~wangwei.cs], would like feedback on changes at https://github.com/nginyc/rafiki/compare/improve_knob_api...improve_model_logging.
Includes shortening/renaming of the API methods, and a rework of the implementation of logging
that streams logs into the DB, allowing app developers to view plots & message logs while
the train job is running. 

> Log visualization API
> ---------------------
>
>                 Key: SINGA-412
>                 URL: https://issues.apache.org/jira/browse/SINGA-412
>             Project: Singa
>          Issue Type: Improvement
>            Reporter: wangwei
>            Priority: Major
>
> The current visualization API in the Rafiki model.py can be simplified.
> {code:java}
> class Logger:
>   ''' For logging data to web front-end.
>   
>   It supports logging text messages via log(prefix), and logging key-value pairs log(**kwargs),
e.g., log(loss=0.1, accuracy=0.4, epoch=1, step=34); To visualize the data on the web page,
the plot has to be defined before logging the data via define_plot(). 
>   TODO log (numpy) array.
>   Example:
>       log = Logger()
>       log.log('start training')
>       log.define_plot('train loss and accuracy', yaxes=['loss', 'acc'], xaxis='epoch')
>       for epoch in range(10):
>            log.log(loss=0.1, acc=0.4, epoch=epoch)
>            # or 
>            # log.log(loss=0.1, epoch=epoch)
>            # log.log(acc=0.4, epoch=epoch)
>   '''
>   def define_plot(name, yaxes = ['loss'], xaxis='epoch')
>   ''' define the plot to be visualized in the web page.
>   Args:
>        name: string for plot name.
>        yaxes: a list of string for the names of the items/metrics, e.g., loss, accuracy,
learning rate, etc. One name corresponds to one key in log().
>        xaxis: string for the xaxis, e.g., epoch or step to indicate the progress. It
also corresponds to on key in log(). 
>   '''
>   def log(prefix='', **kwargs)
>   ''' log one piece of msg and key-val pairs.
>      
>   Args:
>         prefix: text string.
>         kwargs: key-value pairs. key is a string and value is a number. To visualize
one key-value, the plot must be defined via define_plot, and the key must be included in the
yaxes, and another key must be the xaxis. For example, the loss and acc in log(loss=0.1, acc=0.4,
epoch=1, step=34) can be visualized in the plot generated by define_plot('loss and acc', yaxes=['loss',
'acc'], xaxis='epoch')
>   '''
> {code}
> For each log entry, we must also keep the time. In the front end, we can plot either
the yaxes-xaxis or yaxes-time.



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