NasBertTrainer<TLabelCol,TTargetsCol> Class
Definition
Important
Some information relates to prerelease product that may be substantially modified before it’s released. Microsoft makes no warranties, express or implied, with respect to the information provided here.
public abstract class NasBertTrainer<TLabelCol,TTargetsCol> : Microsoft.ML.TorchSharp.TorchSharpBaseTrainer<TLabelCol,TTargetsCol>public abstract class NasBertTrainer<TLabelCol,TTargetsCol> : Microsoft.ML.TorchSharp.NasBert.NasBertTrainertype NasBertTrainer<'LabelCol, 'argetsCol> = class
inherit TorchSharpBaseTrainer<'LabelCol, 'argetsCol>type NasBertTrainer<'LabelCol, 'argetsCol> = class
inherit NasBertTrainerPublic MustInherit Class NasBertTrainer(Of TLabelCol, TTargetsCol)
Inherits TorchSharpBaseTrainer(Of TLabelCol, TTargetsCol)Public MustInherit Class NasBertTrainer(Of TLabelCol, TTargetsCol)
Inherits NasBertTrainerType Parameters
- TLabelCol
- TTargetsCol
- Inheritance
-
NasBertTrainer<TLabelCol,TTargetsCol>
- Inheritance
- Derived
Methods
| Fit(IDataView) | |
| Fit(IDataView) | (Inherited from TorchSharpBaseTrainer<TLabelCol,TTargetsCol>) |
| GetOutputSchema(SchemaShape) | |
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. |