Save and load?

[26medias]

Hi,

How do you save and then re-open a trained network?
It doesn't seem to be explained anywhere in the doc.

Thanks.

[DomVinyard]

This would be really useful to know.

Thanks

[johansen]

Also wondering about this. It would be nice not to have to retrain every time you want to use a model.

[joerobmunoz]

The actual models that you train are JSON instances, so it really depends on how you use them. If you're transferring them to the front-end, you'll have to use local storage or something domain specific. Otherwise, you might consider standard node IO or a database.

[DrorSegev]

Its not the saving, but it the time takes to train the data.
Will it be possible to save and load the trained dataset?

[joerobmunoz]

I think I may be misunderstanding the question, so bear with me a sec.

There should be three principal tasks for this:

1. Create a learner type.
2. Train the data (this does not involve changing the actual data).
3. Run a new, prediction data set through the trained model.

The only two things that you wouldn't have saved after completing these tasks is either the model (which you could save as a standard object) or the data that has yet to be run through the predictor.

[DrorSegev]

Thanks.
I meant how do you save the trained model?
Dor

I think I may be misunderstanding the question, so bear with me a sec.

There should be three principal tasks for this:

1. Create a learner type.
2. Train the data (this does not involve changing the actual data).
3. Run a new, prediction data set through the trained model.

The only two things that you wouldn't have saved after completing these
tasks is either the model (which you could save as a standard object) or
the data that has yet to be run through the predictor.

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[joerobmunoz]

Gotcha.

Suppose you create a new learner and train it:
var learner = ml.kmeans.cluster({ // whatever })

You might save it by:

// 1. Stringify it
var learnerAsAString = JSON.stringify(learner);
// 2. Save to whatever medium (e.g. file, db, etc.)

[DrorSegev]

Sweet.
Thanks.

Dor
On Aug 10, 2016 9:16 PM, "joerobmunoz" notifications@github.com wrote:

Gotcha.

Suppose you create a new learner and train it:

var learner = ml.kmeans.cluster({
// whatever
})

You might save it by:

// 1. Stringify it
var learnerAsAString = JSON.stringify(learner);
// 2. Save to whatever medium (e.g. file, db, etc.)

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[26medias]

What about restoring a saved net?

[DrorSegev]

What do you mean by saved net?
On Aug 10, 2016 10:39 PM, "Twenty-Six medias, Inc." <
notifications@github.com> wrote:

What about restoring a saved net?

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[26medias]

You've explained how to export to a string so that it can be saved, but not how to load that string back so that we can work with it again in the future.

[DrorSegev]

I believe you should just use
var svm= JSON.parse(str)
On Aug 10, 2016 10:49 PM, "Twenty-Six medias, Inc." <
notifications@github.com> wrote:

You've explained how to export to a string so that it can be saved, but
not how to load that string back so that we can work with it again in the
future.

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[26medias]

JSON.stringify() returns a JSON object, containing only the data without circular references or methods.

When doing var svm= JSON.parse(str), svm is an object, without any methods besides the default Object methods.

[openSourceBugs]

This feature is totally unsupported at this time. Passing in a new object into mlp.MLP(JSON.parse(str)) will take you down a rabbit hole of "undefined" errors.

[openSourceBugs]

Looking at mlp.js:

                'W': (typeof settings['w_array'] === 'undefined') ? undefined : settings['w_array'][i],
                'b': (typeof settings['b_array'] === 'undefined') ? undefined : settings['b_array'][i]

b_array and w_array are unspecified anywhere in this entire project. Passing in an object with data to mlp.MLP will necessarily fail because b_array and w_array are dead code with no reference anywhere in the project.