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https://issues.apache.org/jira/browse/SINGA-412?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16713679#comment-16713679
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Ngin Yun Chuan commented on SINGA-412:
--------------------------------------

Hi [~wangwei.cs], following the discussion on Friday, I have made some tweaks 
to the model logging API and knobs API. In particular, you can refer to changes 
to the file 
https://github.com/nginyc/rafiki/compare/improve_knob_api...improve_model_logging#diff-01f0705c7399ec317b7b918775eb8ec5.
 `logger` and `dataset_utils` are now module imports instead of instance 
attributes like `self.utils` and `self.logger`. I have also added `FixedKnob`. 

Let me know if the API looks okay now.

> 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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