ModelOperationsCatalog.Save Method
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.
Overloads
| Save(ITransformer, DataViewSchema, Stream) |
Save a transformer model and the schema of the data that was used to train it to the stream. |
| Save(ITransformer, DataViewSchema, String) |
Save a transformer model and the schema of the data that was used to train it to the file. |
| Save<TSource>(ITransformer, IDataLoader<TSource>, Stream) |
Save a transformer model and the loader used to create its input data to the stream. |
| Save<TSource>(ITransformer, IDataLoader<TSource>, String) |
Save a transformer model and the loader used to create its input data to the file. |
Save(ITransformer, DataViewSchema, Stream)
Save a transformer model and the schema of the data that was used to train it to the stream.
public void Save (Microsoft.ML.ITransformer model, Microsoft.ML.DataViewSchema inputSchema, System.IO.Stream stream);member this.Save : Microsoft.ML.ITransformer * Microsoft.ML.DataViewSchema * System.IO.Stream -> unitPublic Sub Save (model As ITransformer, inputSchema As DataViewSchema, stream As Stream)Parameters
- model
- ITransformer
The trained model to be saved. Note that this can be null, as a shorthand
for an empty transformer chain. Upon loading with Load(Stream, DataViewSchema) the returned value will
be an empty TransformerChain<TLastTransformer>.
- inputSchema
- DataViewSchema
The schema of the input to the transformer. This can be null.
- stream
- Stream
A writeable, seekable stream to save to.
Applies to
Save(ITransformer, DataViewSchema, String)
Save a transformer model and the schema of the data that was used to train it to the file.
public void Save (Microsoft.ML.ITransformer model, Microsoft.ML.DataViewSchema inputSchema, string filePath);member this.Save : Microsoft.ML.ITransformer * Microsoft.ML.DataViewSchema * string -> unitPublic Sub Save (model As ITransformer, inputSchema As DataViewSchema, filePath As String)Parameters
- model
- ITransformer
The trained model to be saved. Note that this can be null, as a shorthand
for an empty transformer chain. Upon loading with Load(Stream, DataViewSchema) the returned value will
be an empty TransformerChain<TLastTransformer>.
- inputSchema
- DataViewSchema
The schema of the input to the transformer. This can be null.
- filePath
- String
Path where model should be saved.
Examples
using System;
using System.Collections.Generic;
using System.IO;
using Microsoft.ML;
namespace Samples.Dynamic.ModelOperations
{
public class SaveLoadModel
{
public static void Example()
{
// Create a new ML context, for ML.NET operations. It can be used for
// exception tracking and logging, as well as the source of randomness.
var mlContext = new MLContext();
// Generate sample data.
var data = new List<Data>()
{
new Data() { Value="abc" }
};
// Convert data to IDataView.
var dataView = mlContext.Data.LoadFromEnumerable(data);
var inputColumnName = nameof(Data.Value);
var outputColumnName = nameof(Transformation.Key);
// Transform.
ITransformer model = mlContext.Transforms.Conversion
.MapValueToKey(outputColumnName, inputColumnName).Fit(dataView);
// Save model.
mlContext.Model.Save(model, dataView.Schema, "model.zip");
// Load model.
using (var file = File.OpenRead("model.zip"))
model = mlContext.Model.Load(file, out DataViewSchema schema);
// Create a prediction engine from the model for feeding new data.
var engine = mlContext.Model
.CreatePredictionEngine<Data, Transformation>(model);
var transformation = engine.Predict(new Data() { Value = "abc" });
// Print transformation to console.
Console.WriteLine("Value: {0}\t Key:{1}", transformation.Value,
transformation.Key);
// Value: abc Key:1
}
private class Data
{
public string Value { get; set; }
}
private class Transformation
{
public string Value { get; set; }
public uint Key { get; set; }
}
}
}
Applies to
Save<TSource>(ITransformer, IDataLoader<TSource>, Stream)
Save a transformer model and the loader used to create its input data to the stream.
public void Save<TSource> (Microsoft.ML.ITransformer model, Microsoft.ML.IDataLoader<TSource> loader, System.IO.Stream stream);member this.Save : Microsoft.ML.ITransformer * Microsoft.ML.IDataLoader<'Source> * System.IO.Stream -> unitPublic Sub Save(Of TSource) (model As ITransformer, loader As IDataLoader(Of TSource), stream As Stream)Type Parameters
- TSource
Parameters
- model
- ITransformer
The trained model to be saved. Note that this can be null, as a shorthand
for an empty transformer chain. Upon loading with LoadWithDataLoader(Stream, IDataLoader<IMultiStreamSource>)
the returned value will be an empty TransformerChain<TLastTransformer>.
- loader
- IDataLoader<TSource>
The loader that was used to create data to train the model.
- stream
- Stream
A writeable, seekable stream to save to.
Applies to
Save<TSource>(ITransformer, IDataLoader<TSource>, String)
Save a transformer model and the loader used to create its input data to the file.
public void Save<TSource> (Microsoft.ML.ITransformer model, Microsoft.ML.IDataLoader<TSource> loader, string filePath);member this.Save : Microsoft.ML.ITransformer * Microsoft.ML.IDataLoader<'Source> * string -> unitPublic Sub Save(Of TSource) (model As ITransformer, loader As IDataLoader(Of TSource), filePath As String)Type Parameters
- TSource
Parameters
- model
- ITransformer
The trained model to be saved. Note that this can be null, as a shorthand
for an empty transformer chain. Upon loading with LoadWithDataLoader(Stream, IDataLoader<IMultiStreamSource>)
the returned value will be an empty TransformerChain<TLastTransformer>.
- loader
- IDataLoader<TSource>
The loader that was used to create data to train the model.
- filePath
- String
Path where model should be saved.