TorchSharpBaseTrainer Class
Definition
Important
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public abstract class TorchSharpBaseTrainer : Microsoft.ML.IEstimator<Microsoft.ML.TorchSharp.TorchSharpBaseTransformer>type TorchSharpBaseTrainer = class
interface IEstimator<TorchSharpBaseTransformer>Public MustInherit Class TorchSharpBaseTrainer
Implements IEstimator(Of TorchSharpBaseTransformer)- Inheritance
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TorchSharpBaseTrainer
- Derived
- Implements
Constructors
| TorchSharpBaseTrainer() |
Methods
| Fit(IDataView) | |
| 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. |