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🧹 NeuralNetwork cleanup pt. 3 -- tasks #1410
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# Conflicts: # package-lock.json # package.json
…upport # Conflicts: # package-lock.json
* don't return values which are not used. * renamed some `get` methods to `set`.
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Introduces a level of abstraction for the "task" of the neural network:
getTask.ts
NNTask
which specifies what information a task needs to provide:noTraining
is set.name
(not currently not used, possible 🪓)classification
,regression
, andimageClassification
.imageClassification
uses some of the same functions asclassification
.getSampleData
is only possible in a limited set of circumstances (see issue NN optionnoTraining
is undocumented and buggy #1409), so I'm throwing a lot of specific errors when those circumstances aren't met.getTask
to convert astring
task name into aNNTask
object.NeuralNetwork/index.ts
this.task
with the task object based onoptions.task
. This defaults toregression
which seems to match what was in the default layers before.addDefaultLayers()
andcompile()
which was moved into the task objects. Now we call a function onthis.task
:const layers = this.task.createLayers(inputUnits, hiddenUnits, outputUnits);
const options = this.task.getCompileOptions(this.options.learningRate);
NeuralNetwork/NeuralNetwork.ts
optimizer.call(this, learningRate)
to set thethisArg
on the optimizer doesn't actually make a difference? (Please correct me if I am wrong). I removedsetOptimizerFunction()
, which, despite the name, just creates an optimizer and doesn't set anything. The instantiation of the optimizer is handled in thegetCompileOptions()
function of the task, which gets thelearningRate
as an argument.