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BinaryLoaderSaverCatalog.LoadFromBinary Méthode

Définition

Surcharges

LoadFromBinary(DataOperationsCatalog, IMultiStreamSource)

Chargez un IDataView fichier binaire à partir d’un IMultiStreamSource fichier binaire. Notez que IDataView« sont paresseux, donc aucun chargement réel ne se produit ici, juste la validation du schéma.

LoadFromBinary(DataOperationsCatalog, String)

Chargez un IDataView fichier binaire à partir d’un fichier binaire. Notez que IDataView« sont paresseux, donc aucun chargement réel ne se produit ici, juste la validation du schéma.

LoadFromBinary(DataOperationsCatalog, IMultiStreamSource)

Chargez un IDataView fichier binaire à partir d’un IMultiStreamSource fichier binaire. Notez que IDataView« sont paresseux, donc aucun chargement réel ne se produit ici, juste la validation du schéma.

public static Microsoft.ML.IDataView LoadFromBinary (this Microsoft.ML.DataOperationsCatalog catalog, Microsoft.ML.Data.IMultiStreamSource fileSource);
static member LoadFromBinary : Microsoft.ML.DataOperationsCatalog * Microsoft.ML.Data.IMultiStreamSource -> Microsoft.ML.IDataView
<Extension()>
Public Function LoadFromBinary (catalog As DataOperationsCatalog, fileSource As IMultiStreamSource) As IDataView

Paramètres

catalog
DataOperationsCatalog

Catalogue.

fileSource
IMultiStreamSource

Source de fichier à partir de laquelle charger. Il peut s’agir d’un MultiFileSource, par exemple.

Retours

S’applique à

LoadFromBinary(DataOperationsCatalog, String)

Chargez un IDataView fichier binaire à partir d’un fichier binaire. Notez que IDataView« sont paresseux, donc aucun chargement réel ne se produit ici, juste la validation du schéma.

public static Microsoft.ML.IDataView LoadFromBinary (this Microsoft.ML.DataOperationsCatalog catalog, string path);
static member LoadFromBinary : Microsoft.ML.DataOperationsCatalog * string -> Microsoft.ML.IDataView
<Extension()>
Public Function LoadFromBinary (catalog As DataOperationsCatalog, path As String) As IDataView

Paramètres

catalog
DataOperationsCatalog

Catalogue.

path
String

Chemin d’accès au fichier à charger.

Retours

Exemples

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; }
        }
    }
}

S’applique à