SentenceSimilarityTrainer Class

Definition

Namespace:: Microsoft.ML.TorchSharp.NasBert

Assembly:: Microsoft.ML.TorchSharp.dll

Package:: Microsoft.ML.TorchSharp v0.22.1

Package:: Microsoft.ML.TorchSharp v0.20.1

Package:: Microsoft.ML.TorchSharp v0.22.0

Package:: Microsoft.ML.TorchSharp v0.23.0-preview.1.25125.4

Source:: SentenceSimilarityTrainer.cs

Source:: SentenceSimilarityTrainer.cs

Source:: SentenceSimilarityTrainer.cs

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.

Represents the IEstimator for training a Deep Neural Network (DNN) to determine sentence similarity.

public class SentenceSimilarityTrainer : Microsoft.ML.TorchSharp.NasBert.NasBertTrainer

type SentenceSimilarityTrainer = class
    inherit NasBertTrainer

Public Class SentenceSimilarityTrainer
Inherits NasBertTrainer(Of Single, Single)

Inheritance: Object

TorchSharpBaseTrainer

TorchSharpBaseTrainer

NasBertTrainer<Single,Single>
SentenceSimilarityTrainer

Inheritance: Object

NasBertTrainer

NasBertTrainer<Single,Single>
SentenceSimilarityTrainer

Remarks

To create this trainer, use TextClassification.

Input and output columns

The input label column data must be type Single and the sentence columns must be of type TextDataViewType.

This trainer outputs the following columns:

Output column name	Column type	Description
`Score`	Single	The degree of similarity between the two sentences.

Trainer characteristics

Characteristic	Value
Machine learning task	Regression
Is normalization required?	No
Is caching required?	No
Required NuGet in addition to Microsoft.ML	Microsoft.ML.TorchSharp and libtorch-cpu or libtorch-cuda-11.3 or any of the OS specific variants.
Exportable to ONNX	No

Training algorithm details

Trains a Deep Neural Network (DNN) by leveraging an existing, pretrained NAS-BERT roBERTa model for the purpose of determining sentence similarity.

Methods

Name	Description
Fit(IDataView)	(Inherited from NasBertTrainer)
GetOutputSchema(SchemaShape)	(Inherited from NasBertTrainer)

Extension Methods

Name	Description
AppendCacheCheckpoint(IEstimator, 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(IEstimator, Action)	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 are often formed into pipelines with many objects, so we may need to build a chain of estimators via EstimatorChain 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.

Name

Description

AppendCacheCheckpoint(IEstimator, 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(IEstimator, Action)

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 are often formed into pipelines with many objects, so we may need to build a chain of estimators via EstimatorChain 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