| File: CodeGenerator\CSharp\CodeGeneratorSettings.cs | Web Access |
| Project: src\src\Microsoft.ML.CodeGenerator\Microsoft.ML.CodeGenerator.csproj (Microsoft.ML.CodeGenerator) |
// Licensed to the .NET Foundation under one or more agreements. // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. using System.Collections; using System.Collections.Generic; using Microsoft.ML.AutoML; using Microsoft.ML.Data; namespace Microsoft.ML.CodeGenerator.CSharp { internal class CodeGeneratorSettings { public CodeGeneratorSettings() { // Set default value Target = GenerateTarget.Cli; OnnxInputMapping = new Dictionary<string, ColumnMapping>(); ClassificationLabel = new string[] { }; ObjectLabel = new string[] { }; } public string LabelName { get; set; } /// <summary> /// mlnet model name /// </summary> public string ModelName { get; set; } /// <summary> /// onnx model name /// </summary> public string OnnxModelName { get; set; } /// <summary> /// classification label /// for Azure image only /// </summary> public string[] ClassificationLabel { get; set; } public string[] ObjectLabel { get; set; } public string OutputName { get; set; } public string OutputBaseDir { get; set; } public string TrainDataset { get; set; } public string TestDataset { get; set; } public GenerateTarget Target { get; set; } public string StablePackageVersion { get; set; } public string UnstablePackageVersion { get; set; } public string OnnxRuntimePackageVersion { get; set; } public bool IsAzureAttach { get; set; } public bool IsImage { get; set; } public bool IsObjectDetection { get; set; } public IDictionary<string, ColumnMapping> OnnxInputMapping { get; set; } internal TaskKind MlTask { get; set; } /// <summary> /// For onnx model only /// </summary> public struct ColumnMapping { /// <summary> /// Mapping Column Name /// </summary> public string ColumnName; /// <summary> /// Mapping Column Type /// </summary> public DataKind ColumnType; } } internal enum GenerateTarget { ModelBuilder = 0, Cli = 1, } }