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DEEP-13, DEEP-39 AI Model completely reimplemented. Dashboard UI implemented. Namespace style changed

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This commit is contained in:
Andrey Shabarshov 2023-07-30 16:20:41 +01:00
parent af6c75a5ac
commit bfb3de9331
36 changed files with 1180 additions and 1088 deletions
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5
DeepTrace/Controllers/DownloadController.cs
View File

@ -2,8 +2,8 @@
using Microsoft.AspNetCore.Mvc;
using System.Text;
namespace DeepTrace.Controllers
{
namespace DeepTrace.Controllers;
[ApiController]
[Route("api/[controller]")]
public class DownloadController : Controller
@ -28,4 +28,3 @@ namespace DeepTrace.Controllers
};
}
}
}

28
DeepTrace/Controls/ModelCard.razor
View File

@ -7,10 +7,16 @@
@inject IDialogService DialogService
@inject IModelStorageService ModelService
@inject ITrainedModelStorageService TrainedModelService
@inject ILogger<MLProcessor> MLProcessorLogger
@inject ILogger<ModelCard> Logger
@inject IMLProcessorFactory MlProcessorFactory
<MudCard Class="mb-3">
<style>
.card {
max-width: 250pt;
}
</style>
<MudCard Class="card mb-3">
<MudCardHeader>
<CardHeaderContent>
<MudText Typo="Typo.h6">@Model?.Name</MudText>
@ -21,6 +27,7 @@
</MudCardHeader>
<MudCardContent>
<MudText>Current state: @_prediction.PredictedLabel</MudText>
<MudText>@_updated.ToString("HH:mm:ss")</MudText>
</MudCardContent>
</MudCard>
@ -30,6 +37,8 @@
private ModelDefinition _modelDefinition = new();
private Prediction _prediction = new();
private IMLProcessor? _mlProcessor;
private DateTime _updated = DateTime.MinValue;
protected override async Task OnAfterRenderAsync(bool firstRender)
{
@ -38,6 +47,7 @@
return;
}
_modelDefinition = (await ModelService.Load(Model.Id)) ?? _modelDefinition;
_mlProcessor = MlProcessorFactory.Create();
#pragma warning disable CS4014
Task.Run(PredictionLoop);
@ -87,15 +97,20 @@
await PredictAnomaly(startDate, endDate);
startDate = endDate;
}
catch(Exception)
catch(Exception e)
{
//ignore
Logger.LogError(e, e.Message);
}
}
}
private async Task PredictAnomaly(DateTime startDate, DateTime endDate)
{
if (Model == null || !Model.IsEnabled)
{
_prediction = new Prediction { PredictedLabel = "Idle" };
return;
}
// use automatic step value to always request 500 elements
var seconds = (endDate - startDate).TotalSeconds / 500.0;
@ -150,8 +165,9 @@
);
}
var mlProcessor = new MLProcessor(MLProcessorLogger);
_prediction = await mlProcessor.Predict(Model, _modelDefinition, data);
_prediction = await _mlProcessor!.Predict(Model, _modelDefinition, data);
_updated = DateTime.Now;
await InvokeAsync(StateHasChanged);
}
private async Task ShowError(string text)

21
DeepTrace/Controls/TrainingDialog.razor
View File

@ -14,12 +14,12 @@
<h4>@Text</h4>
<MudTextField T="string" ReadOnly="true" Text="@_progressText"></MudTextField>
@if (_isTraining == false)
@if (_isTraining == false && _evaluationMetrics != null)
{
<MudText>MicroAccuracy: @_evaluationMetrics!.MicroAccuracy.ToString("N2")</MudText>
<MudText>MacroAccuracy: @_evaluationMetrics!.MacroAccuracy.ToString("N2")</MudText>
<MudText>LogLoss: @_evaluationMetrics!.LogLoss.ToString("N2")</MudText>
<MudText>LogLossReduction: @_evaluationMetrics!.LogLossReduction.ToString("N2")</MudText>
<MudText>MicroAccuracy: @_evaluationMetrics.MicroAccuracy.ToString("N6")</MudText>
<MudText>MacroAccuracy: @_evaluationMetrics.MacroAccuracy.ToString("N6")</MudText>
<MudText>LogLoss: @_evaluationMetrics.LogLoss.ToString("N6")</MudText>
<MudText>LogLossReduction: @_evaluationMetrics.LogLossReduction.ToString("N6")</MudText>
}
@ -47,10 +47,21 @@
return;
}
try
{
_evaluationMetrics = await Processor.Train(Model, UpdateProgress);
}
catch (Exception e)
{
_progressText = "ERROR: " + e.Message;
}
finally
{
_isTraining = false;
await InvokeAsync(StateHasChanged);
}
}
private async void UpdateProgress(string message)
{

51
DeepTrace/Data/DataSourceDefinition.cs
View File

@ -29,4 +29,55 @@ public class DataSourceDefinition
public string Description { get; set; } = string.Empty;
public override string ToString() => Name;
public List<string> GetColumnNames()
{
var measureNames = new[] { "min", "max", "avg", "mean" };
var columnNames = new List<string>();
foreach (var item in Queries)
{
columnNames.AddRange(measureNames.Select(x => $"{item.Query}_{x}"));
}
return columnNames;
}
public static string ConvertToCsv(List<TimeSeriesDataSet> source)
{
var data = "";
for (var i = 0; i < source.Count; i++)
{
var queryData = source[i];
var min = queryData.Data.Min(x => x.Value);
var max = queryData.Data.Max(x => x.Value);
var avg = queryData.Data.Average(x => x.Value);
var mean = queryData.Data.Sum(x => x.Value) / queryData.Data.Count;
data += min + "," + max + "," + avg + "," + mean + ",";
}
return data.TrimEnd(',');
}
public static float[] ToFeatures(List<TimeSeriesDataSet> source)
{
var data = new float[source.Count * 4];
for (var i = 0; i < source.Count; i++)
{
var queryData = source[i];
var min = queryData.Data.Min(x => x.Value);
var max = queryData.Data.Max(x => x.Value);
var avg = queryData.Data.Average(x => x.Value);
var mean = queryData.Data.Sum(x => x.Value) / queryData.Data.Count;
data[i*4 + 0] = min;
data[i*4 + 1] = max;
data[i*4 + 2] = avg;
data[i*4 + 3] = mean;
}
return data;
}
}

5
DeepTrace/Data/IntervalDefinition.cs
View File

@ -1,5 +1,5 @@
namespace DeepTrace.Data
{
namespace DeepTrace.Data;
public class IntervalDefinition
{
public IntervalDefinition() { }
@ -19,4 +19,3 @@
public List<TimeSeriesDataSet> Data { get; set; } = new();
}
}

9
DeepTrace/Data/MLModel1.consumption.cs
View File

@ -5,8 +5,10 @@ using System;
using System.Linq;
using System.IO;
using System.Collections.Generic;
namespace DeepTrace
{
namespace DeepTrace;
#pragma warning disable CS8618 // Non-nullable field must contain a non-null value when exiting constructor. Consider declaring as nullable.
public partial class MLModel1
{
/// <summary>
@ -164,6 +166,8 @@ namespace DeepTrace
#endregion
#pragma warning restore CS8618 // Non-nullable field must contain a non-null value when exiting constructor. Consider declaring as nullable.
private static string MLNetModelPath = Path.GetFullPath("MLModel1.zip");
public static readonly Lazy<PredictionEngine<ModelInput, ModelOutput>> PredictEngine = new Lazy<PredictionEngine<ModelInput, ModelOutput>>(() => CreatePredictEngine(), true);
@ -186,4 +190,3 @@ namespace DeepTrace
return mlContext.Model.CreatePredictionEngine<ModelInput, ModelOutput>(mlModel);
}
}
}

5
DeepTrace/Data/MLModel1.training.cs
View File

@ -9,8 +9,8 @@ using Microsoft.ML.Trainers.FastTree;
using Microsoft.ML.Trainers;
using Microsoft.ML;
namespace DeepTrace
{
namespace DeepTrace;
public partial class MLModel1
{
/// <summary>
@ -61,4 +61,3 @@ namespace DeepTrace
return pipeline;
}
}
}

44
DeepTrace/Data/ModelDefinition.cs
View File

@ -2,6 +2,7 @@
using MongoDB.Bson.Serialization.Attributes;
using MongoDB.Bson;
using System.Text;
using DeepTrace.ML;
namespace DeepTrace.Data;
@ -21,17 +22,10 @@ public class ModelDefinition
public string AIparameters { get; set; } = string.Empty;
public List<IntervalDefinition> IntervalDefinitionList { get; set; } = new();
public List<string> GetColumnNames()
{
var measureNames = new[] { "min", "max", "avg", "mean" };
var columnNames = new List<string>();
foreach (var item in DataSource.Queries)
{
columnNames.AddRange(measureNames.Select(x => $"{item.Query}_{x}"));
}
columnNames.Add("Name");
return columnNames;
}
public List<string> GetColumnNames() => DataSource.GetColumnNames()
.Concat(new[] { "Name" })
.ToList()
;
public string ToCsv()
{
@ -45,30 +39,24 @@ public class ModelDefinition
foreach (var currentInterval in IntervalDefinitionList)
{
var source = currentInterval.Data;
string data = ConvertToCsv(source);
data += "," + currentInterval.Name;
string data = DataSourceDefinition.ConvertToCsv(source);
data += $",\"{currentInterval.Name}\"";
writer.AppendLine(data);
}
return writer.ToString();
}
public static string ConvertToCsv(List<TimeSeriesDataSet> source)
public IEnumerable<MLInputData> ToInput()
{
var data = "";
for (var i = 0; i < source.Count; i++)
foreach (var currentInterval in IntervalDefinitionList)
{
var queryData = source[i];
var min = queryData.Data.Min(x => x.Value);
var max = queryData.Data.Max(x => x.Value);
var avg = queryData.Data.Average(x => x.Value);
var mean = queryData.Data.Sum(x => x.Value) / queryData.Data.Count;
data += min + "," + max + "," + avg + "," + mean + ",";
}
return data+"\"ignoreMe\"";
var source = currentInterval.Data;
yield return new MLInputData
{
Features = DataSourceDefinition.ToFeatures(source),
Label = currentInterval.Name
};
}
}
}

8
DeepTrace/Data/Prediction.cs
View File

@ -4,9 +4,9 @@ namespace DeepTrace.Data;
public class Prediction
{
[ColumnName(@"PredictedLabel")]
public string PredictedLabel { get; set; }
[ColumnName("PredictedLabel")]
public string PredictedLabel { get; set; } = string.Empty;
[ColumnName(@"Score")]
public float[] Score { get; set; }
[ColumnName("Score")]
public float[] Score { get; set; } = Array.Empty<float>();
}

6
DeepTrace/Data/TrainedModelDefinition.cs
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@ -1,14 +1,14 @@
using MongoDB.Bson.Serialization.Attributes;
using MongoDB.Bson;
namespace DeepTrace.Data
{
namespace DeepTrace.Data;
public class TrainedModelDefinition
{
[BsonId]
public ObjectId? Id { get; set; }
public bool IsEnabled { get; set; } = false;
public string Name { get; set; } = string.Empty;
public DataSourceDefinition? DataSource{ get; set;}
public byte[] Value { get; set; } = Array.Empty<byte>(); //base64
}
}

50
DeepTrace/ML/EstimatorBuilder.cs
View File

@ -1,47 +1,31 @@
using DeepTrace.Data;
using Microsoft.ML;
using Microsoft.ML.Data;
using Microsoft.ML.Trainers;
namespace DeepTrace.ML
{
namespace DeepTrace.ML;
public class EstimatorBuilder : IEstimatorBuilder
{
public IEstimator<ITransformer> BuildPipeline(MLContext mlContext, ModelDefinition model)
{
IEstimator<ITransformer>? pipeline = null;
var ds = model.DataSource;
var measureNames = new[] { "min", "max", "avg", "mean" };
var columnNames = new List<string>();
foreach (var item in ds.Queries)
return
mlContext.Transforms.NormalizeMinMax(inputColumnName: nameof(MLInputData.Features),outputColumnName: "Features")
.Append(mlContext.Transforms.Conversion.MapValueToKey(inputColumnName: nameof(MLInputData.Label), outputColumnName: "Label"))
// .AppendCacheCheckpoint(mlContext)
.Append(mlContext.MulticlassClassification.Trainers.OneVersusAll(
binaryEstimator: mlContext.BinaryClassification.Trainers.LbfgsLogisticRegression(
new LbfgsLogisticRegressionBinaryTrainer.Options
{
var estimators = measureNames.Select(x => mlContext.Transforms.Text.FeaturizeText(inputColumnName: $"{item.Query}_{x}", outputColumnName: $"{item.Query}_{x}"));
columnNames.AddRange(measureNames.Select(x => $"{item.Query}_{x}"));
foreach (var e in estimators)
{
if (pipeline == null)
{
pipeline = e;
L1Regularization = 1F,
L2Regularization = 1F,
LabelColumnName = "Label",
FeatureColumnName = "Features"
}
else
{
pipeline = pipeline.Append(e);
}
}
}
pipeline = pipeline!
.Append(mlContext.Transforms.Concatenate(@"Features", columnNames.ToArray()))
.Append(mlContext.Transforms.Conversion.MapValueToKey(outputColumnName: @"Name", inputColumnName: @"Name"))
.Append(mlContext.Transforms.NormalizeMinMax(@"Features", @"Features"))
.Append(mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryEstimator: mlContext.BinaryClassification.Trainers.LbfgsLogisticRegression(new LbfgsLogisticRegressionBinaryTrainer.Options() { L1Regularization = 1F, L2Regularization = 1F, LabelColumnName = @"Name", FeatureColumnName = @"Features" }), labelColumnName: @"Name"))
.Append(mlContext.Transforms.Conversion.MapKeyToValue(outputColumnName: @"PredictedLabel", inputColumnName: @"PredictedLabel"));
return pipeline;
))
)
.Append(mlContext.Transforms.Conversion.MapKeyToValue(nameof(MLOutputData.PredictedLabel), inputColumnName: "PredictedLabel"));
}
}
}

5
DeepTrace/ML/IEstimatorBuilder.cs
View File

@ -1,10 +1,9 @@
using DeepTrace.Data;
using Microsoft.ML;
namespace DeepTrace.ML
{
namespace DeepTrace.ML;
public interface IEstimatorBuilder
{
IEstimator<ITransformer> BuildPipeline(MLContext mlContext, ModelDefinition model);
}
}

5
DeepTrace/ML/IMLProcessor.cs
View File

@ -10,3 +10,8 @@ public interface IMLProcessor
void Import(byte[] data);
Task<Prediction> Predict(TrainedModelDefinition trainedModel, ModelDefinition model, List<TimeSeriesDataSet> data);
}
public interface IMLProcessorFactory
{
IMLProcessor Create();
}

5
DeepTrace/ML/IMeasure.cs
View File

@ -1,11 +1,10 @@
using PrometheusAPI;
namespace DeepTrace.ML
{
namespace DeepTrace.ML;
public interface IMeasure
{
public string Name { get; }
void Reset();
float Calculate(IEnumerable<TimeSeries> data);
}
}

5
DeepTrace/ML/MLEvaluationMetrics.cs
View File

@ -1,5 +1,5 @@
namespace DeepTrace.ML
{
namespace DeepTrace.ML;
public class MLEvaluationMetrics
{
public MLEvaluationMetrics()
@ -13,4 +13,3 @@
public double LogLossReduction { get; set; }
}
}

41
DeepTrace/ML/MLHelpers.cs
View File

@ -7,6 +7,21 @@ namespace DeepTrace.ML;
public record ModelRecord(MLContext Context, DataViewSchema Schema, ITransformer Transformer);
public class MLInputData
{
public string Label { get; set; } = "Normal operation";
public float[] Features { get; set; } = Array.Empty<float>();
}
public class MLOutputData
{
public string PredictedLabel { get; set; } = string.Empty;
public float[] Score { get; set; } = Array.Empty<float>();
}
public static class MLHelpers
{
public static byte[] ExportSingleModel( ModelRecord model)
@ -32,10 +47,22 @@ public static class MLHelpers
await File.WriteAllTextAsync(fileName, csv);
return LoadFromCsv(mlContext, model, fileName);
return (LoadFromCsv(mlContext, model, fileName), fileName);
}
public static (IDataView View, string FileName) LoadFromCsv(MLContext mlContext, ModelDefinition model, string fileName)
public static Task<IDataView> ToInput(MLContext mlContext, ModelDefinition model)
{
var input = model.ToInput().ToList();
// VectorType attribute with dynamic dimension
// https://github.com/dotnet/machinelearning/issues/164
var schemaDef = SchemaDefinition.Create(typeof(MLInputData));
schemaDef["Features"].ColumnType = new VectorDataViewType(NumberDataViewType.Single, input.First().Features.Length );
return Task.FromResult(mlContext.Data.LoadFromEnumerable(input, schemaDef));
}
public static IDataView LoadFromCsv(MLContext mlContext, ModelDefinition model, string fileName)
{
var columnNames = model.GetColumnNames();
var columns = columnNames
@ -43,8 +70,14 @@ public static class MLHelpers
.ToArray()
;
var view = mlContext.Data.LoadFromTextFile(fileName, columns, separatorChar: ',', hasHeader: true, allowQuoting: true, trimWhitespace: true);
var view = mlContext.Data.LoadFromTextFile(
fileName,
columns,
separatorChar: ',',
hasHeader: true,
allowQuoting: true,
trimWhitespace: true);
return (view, fileName);
return view;
}
}

74
DeepTrace/ML/MLProcessor.cs
View File

@ -1,32 +1,51 @@
using DeepTrace.Data;
using Microsoft.ML;
using Microsoft.ML.Data;
using PrometheusAPI;
using System.Data;
using static DeepTrace.MLModel1;
namespace DeepTrace.ML
namespace DeepTrace.ML;
internal class MLProcessorFactory : IMLProcessorFactory
{
private readonly ILogger<MLProcessor> _logger;
private IEstimatorBuilder _estimatorBuilder;
public MLProcessorFactory(ILogger<MLProcessor> logger, IEstimatorBuilder estimatorBuilder)
{
_logger = logger;
_estimatorBuilder = estimatorBuilder;
}
public IMLProcessor Create() => new MLProcessor(_logger, _estimatorBuilder);
}
/// <summary>
/// Wrapper for ML.NET operations.
/// </summary>
public class MLProcessor : IMLProcessor
{
private readonly ILogger<MLProcessor> _logger;
private MLContext _mlContext = new MLContext();
private EstimatorBuilder _estimatorBuilder = new EstimatorBuilder();
private IEstimatorBuilder _estimatorBuilder;
private DataViewSchema? _schema;
private ITransformer? _transformer;
private static string _signature = "DeepTrace-Model-v1-" + typeof(MLProcessor).Name;
private readonly ILogger<MLProcessor> _logger;
private PredictionEngine<MLInputData, MLOutputData>? _predictionEngine;
public MLProcessor(ILogger<MLProcessor> logger)
public MLProcessor(ILogger<MLProcessor> logger, IEstimatorBuilder estimatorBuilder)
{
_logger = logger;
_estimatorBuilder = estimatorBuilder;
}
private string Name { get; set; } = "TestModel";
public async Task<MLEvaluationMetrics> Train(ModelDefinition modelDef, Action<string> log)
{
_logger.LogInformation("Training started");
Name = modelDef.Name;
var pipeline = _estimatorBuilder.BuildPipeline(_mlContext, modelDef);
var (data, filename) = await MLHelpers.Convert(_mlContext, modelDef);
var data = await MLHelpers.ToInput(_mlContext, modelDef);
DataOperationsCatalog.TrainTestData dataSplit = _mlContext.Data.TrainTestSplit(data, testFraction: 0.2);
@ -35,13 +54,13 @@ namespace DeepTrace.ML
{
_schema = data.Schema;
_transformer = pipeline.Fit(dataSplit.TrainSet);
return Evaluate(dataSplit.TestSet);
}
finally
{
File.Delete(filename);
_logger.LogInformation("Training finished");
}
}
private void LogEvents(Action<string> log, LoggingEventArgs e)
@ -56,8 +75,10 @@ namespace DeepTrace.ML
private MLEvaluationMetrics Evaluate(IDataView testData)
{
// https://learn.microsoft.com/en-us/dotnet/api/microsoft.ml.standardtrainerscatalog.lbfgslogisticregression?view=ml-dotnet
var predictions = _transformer!.Transform(testData);
var metrics = _mlContext.MulticlassClassification.Evaluate(predictions, "Name");
var metrics = _mlContext.MulticlassClassification.Evaluate(predictions, nameof(MLInputData.Label));
var evaluationMetrics = new MLEvaluationMetrics()
{
MicroAccuracy = metrics.MicroAccuracy,
@ -110,28 +131,25 @@ namespace DeepTrace.ML
(_mlContext, _schema, _transformer) = MLHelpers.ImportSingleModel(bytes);
}
public async Task<Prediction> Predict(TrainedModelDefinition trainedModel, ModelDefinition model, List<TimeSeriesDataSet> data)
public Task<Prediction> Predict(TrainedModelDefinition trainedModel, ModelDefinition model, List<TimeSeriesDataSet> data)
{
Name = trainedModel.Name;
if (_transformer == null )
Import(trainedModel.Value);
var headers = string.Join(",", model.GetColumnNames().Select(x => $"\"{x}\""));
var row = ModelDefinition.ConvertToCsv(data);
var csv = headers+"\n"+row;
var fileName = Path.GetTempFileName();
try
if (_predictionEngine == null)
{
await File.WriteAllTextAsync(fileName, csv);
var (dataView, _) = MLHelpers.LoadFromCsv(_mlContext, model, fileName);
var predictionEngine = _mlContext.Model.CreatePredictionEngine<IDataView, Prediction>(_transformer);
var prediction = predictionEngine.Predict(dataView);
return prediction;
_predictionEngine = _mlContext.Model.CreatePredictionEngine<MLInputData, MLOutputData>(_transformer, _schema);
}
finally
var input = new MLInputData
{
File.Delete(fileName);
}
}
Features = DataSourceDefinition.ToFeatures(data)
};
var prediction = _predictionEngine.Predict( input );
return Task.FromResult( new Prediction { PredictedLabel = prediction.PredictedLabel, Score = prediction.Score } );
}
}

6
DeepTrace/ML/Measures.cs
View File

@ -1,7 +1,7 @@
using PrometheusAPI;
namespace DeepTrace.ML
{
namespace DeepTrace.ML;
public class MeasureMin : IMeasure
{
public string Name => "Min";
@ -85,5 +85,3 @@ namespace DeepTrace.ML
/// </summary>
public class MeasureDiffSum : MeasureDiff<MeasureSum> { }
public class MeasureDiffMedian : MeasureDiff<MeasureMedian> { }
}

4
DeepTrace/Pages/DataSources.razor
View File

@ -58,8 +58,8 @@
int pos = i;
<MudItem xs="10">
@*<MudTextField Label="Query" @bind-Value="_queryForm.Source.Queries[pos].Query" Variant="Variant.Text" InputType="InputType.Search" Lines="2" />*@
<MudAutocomplete Label="Query" @bind-Value="_queryForm.Source.Queries[pos].Query" Lines="1" Variant="Variant.Text" SearchFunc="@SearchForQuery"></MudAutocomplete>
<MudTextField Label="Query" @bind-Value="_queryForm.Source.Queries[pos].Query" Variant="Variant.Text" InputType="InputType.Search" Lines="2" />
@*<MudAutocomplete Label="Query" @bind-Value="_queryForm.Source.Queries[pos].Query" Lines="1" Variant="Variant.Text" SearchFunc="@SearchForQuery"></MudAutocomplete>*@
</MudItem>
<MudItem xs="1">
<MudIconButton Icon="@Icons.Material.Outlined.Add" Variant="Variant.Outlined" aria-label="add" OnClick="@(() => AddQuery(pos))" />

5
DeepTrace/Pages/Error.cshtml.cs
View File

@ -2,8 +2,8 @@
using Microsoft.AspNetCore.Mvc.RazorPages;
using System.Diagnostics;
namespace DeepTrace.Pages
{
namespace DeepTrace.Pages;
[ResponseCache(Duration = 0, Location = ResponseCacheLocation.None, NoStore = true)]
[IgnoreAntiforgeryToken]
public class ErrorModel : PageModel
@ -24,4 +24,3 @@ namespace DeepTrace.Pages
RequestId = Activity.Current?.Id ?? HttpContext.TraceIdentifier;
}
}
}

9
DeepTrace/Pages/Training.razor
View File

@ -18,7 +18,7 @@
@inject IEstimatorBuilder EstimatorBuilder
@inject NavigationManager NavManager
@inject IJSRuntime Js
@inject ILogger<MLProcessor> MLProcessorLogger
@inject IMLProcessorFactory MlProcessorFactory
<PageTitle>Training</PageTitle>
@ -531,14 +531,14 @@
private async Task HandleTrain()
{
var mlProcessor = new MLProcessor(MLProcessorLogger);
MLProcessorLogger.LogInformation("Training started");
var options = new DialogOptions
{
CloseOnEscapeKey = true
};
var parameters = new DialogParameters();
var mlProcessor = MlProcessorFactory.Create();
parameters.Add(nameof(Controls.TrainingDialog.Text), _modelForm!.CurrentModel.Name);
parameters.Add(nameof(Controls.TrainingDialog.Processor), mlProcessor);
parameters.Add(nameof(Controls.TrainingDialog.Model), _modelForm.CurrentModel);
@ -546,7 +546,6 @@
var d = DialogService.Show<Controls.TrainingDialog>("Training", parameters, options);
var res = await d.Result;
MLProcessorLogger.LogInformation("Training finished");
var bytes = mlProcessor.Export();
//save to Mongo

1
DeepTrace/Program.cs
View File

@ -29,6 +29,7 @@ builder.Services
.AddSingleton<IModelStorageService, ModelStorageService>()
.AddSingleton<ITrainedModelStorageService, TrainedModelStorageService>()
.AddSingleton<IEstimatorBuilder, EstimatorBuilder>()
.AddSingleton<IMLProcessorFactory, MLProcessorFactory>()
;
var app = builder.Build();

5
DeepTrace/Services/DataSourceStorageService.cs
View File

@ -1,8 +1,8 @@
using MongoDB.Bson;
using MongoDB.Driver;
namespace DeepTrace.Services
{
namespace DeepTrace.Services;
public class DataSourceStorageService : IDataSourceStorageService
{
@ -55,4 +55,3 @@ namespace DeepTrace.Services
await collection.DeleteOneAsync($"_id = {source.Id}");
}
}
}

5
DeepTrace/Services/IDataSourceStorageService.cs
View File

@ -2,8 +2,8 @@
using MongoDB.Bson.Serialization.Attributes;
using MongoDB.Bson;
namespace DeepTrace.Services
{
namespace DeepTrace.Services;
public class DataSourceStorage : DataSourceDefinition, IEquatable<DataSourceStorage>
{
[BsonId]
@ -35,4 +35,3 @@ namespace DeepTrace.Services
Task<List<DataSourceStorage>> Load();
Task Store(DataSourceStorage source);
}
}

5
DeepTrace/Services/IModelStorageService.cs
View File

@ -3,8 +3,8 @@ using MongoDB.Bson;
using DeepTrace.Data;
using System.Text;
namespace DeepTrace.Services
{
namespace DeepTrace.Services;
public interface IModelStorageService
{
@ -13,4 +13,3 @@ namespace DeepTrace.Services
Task<ModelDefinition?> Load(BsonObjectId id);
Task Store(ModelDefinition source);
}
}

5
DeepTrace/Services/ITrainedModelStorageService.cs
View File

@ -1,11 +1,10 @@
using DeepTrace.Data;
namespace DeepTrace.Services
{
namespace DeepTrace.Services;
public interface ITrainedModelStorageService
{
Task Delete(TrainedModelDefinition source, bool ignoreNotStored = false);
Task<List<TrainedModelDefinition>> Load();
Task Store(TrainedModelDefinition source);
}
}

10
DeepTrace/Services/ModelStorageService.cs
View File

@ -2,8 +2,8 @@
using MongoDB.Bson;
using MongoDB.Driver;
namespace DeepTrace.Services
{
namespace DeepTrace.Services;
public class ModelStorageService : IModelStorageService
{
@ -30,8 +30,9 @@ namespace DeepTrace.Services
{
var db = _client.GetDatabase(MongoDBDatabaseName);
var collection = db.GetCollection<ModelDefinition>(MongoDBCollection);
var res = (await (await collection.FindAsync($"{{_id:ObjectId(\"{id}\")}}")).ToListAsync()).FirstOrDefault();
return res;
var res = await (await collection.FindAsync($"{{ _id : ObjectId(\"{id}\") }}")).ToListAsync();
return res.FirstOrDefault();
}
public async Task Store(ModelDefinition source)
@ -65,4 +66,3 @@ namespace DeepTrace.Services
await collection.DeleteOneAsync(filter: new BsonDocument("_id", source.Id));
}
}
}

5
DeepTrace/Services/TrainedModelStorageService.cs
View File

@ -2,8 +2,8 @@
using MongoDB.Bson;
using MongoDB.Driver;
namespace DeepTrace.Services
{
namespace DeepTrace.Services;
public class TrainedModelStorageService: ITrainedModelStorageService
{
private const string MongoDBDatabaseName = "DeepTrace";
@ -55,4 +55,3 @@ namespace DeepTrace.Services
await collection.DeleteOneAsync(filter: new BsonDocument("_id", source.Id));
}
}
}

5
PrometheusAPI/JsonSetializerSetup.cs
View File

@ -6,8 +6,8 @@ using System.Text.Json.Serialization;
using System.Text.Json;
using System.Threading.Tasks;
namespace PrometheusAPI
{
namespace PrometheusAPI;
public static class JsonSetializerSetup
{
private static JsonSerializerOptions _options = new JsonSerializerOptions
@ -22,4 +22,3 @@ namespace PrometheusAPI
public static JsonSerializerOptions Options => _options;
}
}

5
PrometheusAPI/PrometheusClient.cs
View File

@ -1,7 +1,7 @@
using System.Text.Json;
namespace PrometheusAPI
{
namespace PrometheusAPI;
public class PrometheusClient
{
private readonly HttpClient _client;
@ -116,4 +116,3 @@ namespace PrometheusAPI
}
}
}

5
PrometheusAPI/TimeSeriesCoverter.cs
View File

@ -1,8 +1,8 @@
using System.Text.Json;
using System.Text.Json.Serialization;
namespace PrometheusAPI
{
namespace PrometheusAPI;
internal class TimeSeriesCoverter : JsonConverter<TimeSeries?>
{
public override TimeSeries? Read(ref Utf8JsonReader reader, Type typeToConvert, JsonSerializerOptions options)
@ -49,4 +49,3 @@ namespace PrometheusAPI
}
}
}