BinaryLoaderSaverCatalog.SaveAsBinary Metodo

Definizione

Spazio dei nomi:

Microsoft.ML

Assembly:

Microsoft.ML.Data.dll

Pacchetto:

Microsoft.ML v3.0.1

Salvare in IDataView un flusso binario.

public static void SaveAsBinary (this Microsoft.ML.DataOperationsCatalog catalog, Microsoft.ML.IDataView data, System.IO.Stream stream, bool keepHidden = false);

static member SaveAsBinary : Microsoft.ML.DataOperationsCatalog * Microsoft.ML.IDataView * System.IO.Stream * bool -> unit

<Extension()>
Public Sub SaveAsBinary (catalog As DataOperationsCatalog, data As IDataView, stream As Stream, Optional keepHidden As Boolean = false)

Parametri

catalog

DataOperationsCatalog

Catalogo.

data

IDataView

Visualizzazione dati da salvare.

stream

Stream

Flusso in cui scrivere.

keepHidden

Boolean

Indica se mantenere le colonne nascoste nel set di dati.

Esempio

using System;
using System.Collections.Generic;
using System.IO;
using Microsoft.ML;

namespace Samples.Dynamic
{
    public static class SaveAndLoadFromBinary
    {
        public static void Example()
        {
            // Create a new context for ML.NET operations. It can be used for
            // exception tracking and logging, as a catalog of available operations
            // and as the source of randomness. Setting the seed to a fixed number
            // in this example to make outputs deterministic.
            var mlContext = new MLContext(seed: 0);

            // Create a list of training data points.
            var dataPoints = new List<DataPoint>()
            {
                new DataPoint(){ Label = 0, Features = 4},
                new DataPoint(){ Label = 0, Features = 5},
                new DataPoint(){ Label = 0, Features = 6},
                new DataPoint(){ Label = 1, Features = 8},
                new DataPoint(){ Label = 1, Features = 9},
            };

            // Convert the list of data points to an IDataView object, which is
            // consumable by ML.NET API.
            IDataView data = mlContext.Data.LoadFromEnumerable(dataPoints);

            // Create a FileStream object and write the IDataView to it as a binary
            // IDV file. 
            using (FileStream stream = new FileStream("data.idv", FileMode.Create))
                mlContext.Data.SaveAsBinary(data, stream);

            // Create an IDataView object by loading the binary IDV file.
            IDataView loadedData = mlContext.Data.LoadFromBinary("data.idv");

            // Inspect the data that is loaded from the previously saved binary file
            var loadedDataEnumerable = mlContext.Data
                .CreateEnumerable<DataPoint>(loadedData, reuseRowObject: false);

            foreach (DataPoint row in loadedDataEnumerable)
                Console.WriteLine($"{row.Label}, {row.Features}");

            // Preview of the loaded data.
            // 0, 4
            // 0, 5
            // 0, 6
            // 1, 8
            // 1, 9
        }

        // Example with label and feature values. A data set is a collection of such
        // examples.
        private class DataPoint
        {
            public float Label { get; set; }

            public float Features { get; set; }
        }
    }
}