BinaryLoaderSaverCatalog.LoadFromBinary Metode

Definisi

Ruang nama:

Microsoft.ML

Rakitan:

Microsoft.ML.Data.dll

Paket:

Microsoft.ML v3.0.1

Overload

LoadFromBinary(DataOperationsCatalog, IMultiStreamSource)	IDataView Memuat dari IMultiStreamSource pada file biner. Perhatikan bahwa IDataViewmalas, jadi tidak ada pemuatan aktual yang terjadi di sini, hanya validasi skema.
LoadFromBinary(DataOperationsCatalog, String)	IDataView Memuat dari file biner. Perhatikan bahwa IDataViewmalas, jadi tidak ada pemuatan aktual yang terjadi di sini, hanya validasi skema.

LoadFromBinary(DataOperationsCatalog, IMultiStreamSource)

IDataView Memuat dari IMultiStreamSource pada file biner. Perhatikan bahwa IDataViewmalas, jadi tidak ada pemuatan aktual yang terjadi di sini, hanya validasi skema.

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

Parameter

catalog

DataOperationsCatalog

Katalognya.

fileSource

IMultiStreamSource

Sumber file yang akan dimuat. Ini bisa menjadi MultiFileSource, misalnya.

Mengembalikan

IDataView

LoadFromBinary(DataOperationsCatalog, String)

IDataView Memuat dari file biner. Perhatikan bahwa IDataViewmalas, jadi tidak ada pemuatan aktual yang terjadi di sini, hanya validasi skema.

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

Parameter

catalog

DataOperationsCatalog

Katalognya.

path

String

Jalur ke file yang akan dimuat.

Mengembalikan

IDataView

Contoh

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; }
        }
    }
}