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TorchSharpBaseTrainer<TLabelCol,TTargetsCol> Class

Definition

public abstract class TorchSharpBaseTrainer<TLabelCol,TTargetsCol> : Microsoft.ML.TorchSharp.TorchSharpBaseTrainer
type TorchSharpBaseTrainer<'LabelCol, 'argetsCol> = class
    inherit TorchSharpBaseTrainer
Public MustInherit Class TorchSharpBaseTrainer(Of TLabelCol, TTargetsCol)
Inherits TorchSharpBaseTrainer

Type Parameters

TLabelCol
TTargetsCol
Inheritance
TorchSharpBaseTrainer<TLabelCol,TTargetsCol>
Derived

Methods

Fit(IDataView)
GetOutputSchema(SchemaShape) (Inherited from TorchSharpBaseTrainer)

Extension Methods

AppendCacheCheckpoint<TTrans>(IEstimator<TTrans>, IHostEnvironment)

Append a 'caching checkpoint' to the estimator chain. This will ensure that the downstream estimators will be trained against cached data. It is helpful to have a caching checkpoint before trainers that take multiple data passes.

WithOnFitDelegate<TTransformer>(IEstimator<TTransformer>, Action<TTransformer>)

Given an estimator, return a wrapping object that will call a delegate once Fit(IDataView) is called. It is often important for an estimator to return information about what was fit, which is why the Fit(IDataView) method returns a specifically typed object, rather than just a general ITransformer. However, at the same time, IEstimator<TTransformer> are often formed into pipelines with many objects, so we may need to build a chain of estimators via EstimatorChain<TLastTransformer> where the estimator for which we want to get the transformer is buried somewhere in this chain. For that scenario, we can through this method attach a delegate that will be called once fit is called.

Applies to