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DEEP-14 Interval import implemented. Training dialog added. Logging added

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This commit is contained in:
Andrey Shabarshov 2023-07-25 17:21:06 +01:00
parent 0b26c25620
commit facecd5ed7
16 changed files with 340 additions and 94 deletions
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16
DeepTrace/Controls/Dialog.razor
View File

@ -3,18 +3,32 @@
@Text
</DialogContent>
<DialogActions>
@if (AllowCancel)
@if( IsYesNoCancel )
{
<MudButton Color="MudBlazor.Color.Primary" OnClick="Yes">Yes</MudButton>
<MudButton OnClick="No">No</MudButton>
<MudButton OnClick="Cancel">Cancel</MudButton>
}
else
{
if (AllowCancel)
{
<MudButton OnClick="Cancel">Cancel</MudButton>
}
<MudButton Color="MudBlazor.Color.Primary" OnClick="Submit">Ok</MudButton>
}
</DialogActions>
</MudDialog>
@code {
[CascadingParameter] MudDialogInstance? MudDialog { get; set; }
[Parameter] public bool AllowCancel { get; set; }
[Parameter] public string Text { get; set; } = "";
[Parameter] public bool IsYesNoCancel { get; set; } = false;
void Submit() => MudDialog?.Close(DialogResult.Ok(true));
void Cancel() => MudDialog?.Cancel();
void Yes() => MudDialog?.Close(DialogResult.Ok(true));
void No() => MudDialog?.Close(DialogResult.Ok(false));
}

51
DeepTrace/Controls/TrainingDialog.razor Normal file
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@ -0,0 +1,51 @@
@using DeepTrace.Data;
@using DeepTrace.ML;
<style>
.dialog-content{
min-width: 1000px;
width: fit-content;
}
</style>
<MudDialog Class="dialog-content">
<DialogContent>
<h4>@Text</h4>
<MudTextField T="string" ReadOnly="true" Text="@_progressText"></MudTextField>
</DialogContent>
<DialogActions>
<MudButton Color="MudBlazor.Color.Primary" OnClick="Submit" Disabled="@_isTraining">Ok</MudButton>
</DialogActions>
</MudDialog>
@code {
[CascadingParameter] MudDialogInstance? MudDialog { get; set; }
[Parameter] public MLProcessor? Processor { get; set; }
[Parameter] public ModelDefinition? Model { get; set; }
[Parameter] public string Text { get; set; } = "";
private string _progressText = "";
private bool _isTraining = true;
void Submit() => MudDialog?.Close(DialogResult.Ok(true));
protected override async Task OnAfterRenderAsync(bool firstRender)
{
if (!firstRender || Processor==null || Model==null)
{
return;
}
await Processor.Train(Model, UpdateProgress);
_isTraining = false;
await InvokeAsync(StateHasChanged);
}
private async void UpdateProgress(string message)
{
_progressText = message;
await InvokeAsync(StateHasChanged);
}
}

2
DeepTrace/Data/IntervalDefinition.cs
View File

@ -16,7 +16,7 @@
public string Name { get; set; } = string.Empty;
public List<TimeSeriesDataSet> Data { get; set; }
public List<TimeSeriesDataSet> Data { get; set; } = new();
}
}

73
DeepTrace/Data/MLModel1.mbconfig
View File

@ -191,50 +191,50 @@
"Version": 0,
"Type": "Trial",
"TrainerName": "SdcaMaximumEntropyMulti",
"Score": 0.87460317460317472,
"RuntimeInSeconds": 5.47599983215332
},
{
"Version": 0,
"Type": "Trial",
"TrainerName": "FastForestOva",
"Score": 0.91460317460317475,
"RuntimeInSeconds": 3.6610000133514404
"Score": 0.57954545454545447,
"RuntimeInSeconds": 5.3579998016357422
},
{
"Version": 0,
"Type": "Trial",
"TrainerName": "FastTreeOva",
"Score": 0.91460317460317475,
"RuntimeInSeconds": 3.2239999771118164
"Score": 0.91090909090909089,
"RuntimeInSeconds": 3.3050000667572021
},
{
"Version": 0,
"Type": "Trial",
"TrainerName": "LbfgsLogisticRegressionOva",
"Score": 0.96035353535353529,
"RuntimeInSeconds": 2.812000036239624
},
{
"Version": 0,
"Type": "Trial",
"TrainerName": "SdcaLogisticRegressionOva",
"Score": 0.87460317460317472,
"RuntimeInSeconds": 7.8530001640319824
"TrainerName": "FastTreeOva",
"Score": 0.96460317460317468,
"RuntimeInSeconds": 3.1909999847412109
},
{
"Version": 0,
"Type": "Trial",
"TrainerName": "LbfgsMaximumEntropyMulti",
"Score": 0.96035353535353529,
"RuntimeInSeconds": 2.3250000476837158
"Score": 0.95031746031746034,
"RuntimeInSeconds": 2.2969999313354492
},
{
"Version": 0,
"Type": "Trial",
"TrainerName": "LightGbmMulti",
"Score": 0.91460317460317475,
"RuntimeInSeconds": 2.875
"TrainerName": "FastForestOva",
"Score": 0.91090909090909089,
"RuntimeInSeconds": 3.9630000591278076
},
{
"Version": 0,
"Type": "Trial",
"TrainerName": "SdcaLogisticRegressionOva",
"Score": 0.57954545454545447,
"RuntimeInSeconds": 7.7239999771118164
},
{
"Version": 0,
"Type": "Trial",
"TrainerName": "LbfgsLogisticRegressionOva",
"Score": 0.95031746031746034,
"RuntimeInSeconds": 3.937000036239624
}
],
"Pipeline": {
@ -311,20 +311,16 @@
"OutputColumnName": "Q1mean"
},
"20": {
"OutputColumnNames": [
"Features"
],
"InputColumnNames": [
"Features"
]
},
"21": {
"L1Regularization": 1.0,
"L2Regularization": 1.0,
"NumberOfLeaves": 33,
"MinimumExampleCountPerLeaf": 14,
"NumberOfTrees": 4,
"MaximumBinCountPerFeature": 1022,
"FeatureFraction": 0.99999999,
"LearningRate": 0.75792684413443268,
"LabelColumnName": "Name",
"FeatureColumnName": "Features"
},
"22": {
"21": {
"OutputColumnName": "PredictedLabel",
"InputColumnName": "PredictedLabel"
},
@ -378,8 +374,7 @@
"FeaturizeText",
"Concatenate",
"MapValueToKey",
"NormalizeMinMax",
"LbfgsLogisticRegressionOva",
"FastTreeOva",
"MapKeyToValue"
]
},

4
DeepTrace/Data/MLModel1.training.cs
View File

@ -5,6 +5,7 @@ using System.Linq;
using System.Text;
using System.Threading.Tasks;
using Microsoft.ML.Data;
using Microsoft.ML.Trainers.FastTree;
using Microsoft.ML.Trainers;
using Microsoft.ML;
@ -54,8 +55,7 @@ namespace DeepTrace
.Append(mlContext.Transforms.Text.FeaturizeText(inputColumnName:@"Q5mean",outputColumnName:@"Q5mean"))
.Append(mlContext.Transforms.Concatenate(@"Features", new []{@"Q1max",@"Q1avg",@"Q1mean",@"Q2min",@"Q2max",@"Q2avg",@"Q2mean",@"Q3min",@"Q3max",@"Q3avg",@"Q3mean",@"Q4max",@"Q4avg",@"Q4mean",@"Q5min",@"Q5max",@"Q5avg",@"Q5mean"}))
.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.MulticlassClassification.Trainers.OneVersusAll(binaryEstimator:mlContext.BinaryClassification.Trainers.FastTree(new FastTreeBinaryTrainer.Options(){NumberOfLeaves=33,MinimumExampleCountPerLeaf=14,NumberOfTrees=4,MaximumBinCountPerFeature=1022,FeatureFraction=0.99999999,LearningRate=0.757926844134433,LabelColumnName=@"Name",FeatureColumnName=@"Features"}),labelColumnName: @"Name"))
.Append(mlContext.Transforms.Conversion.MapKeyToValue(outputColumnName:@"PredictedLabel",inputColumnName:@"PredictedLabel"));
return pipeline;

4
DeepTrace/Data/TrainedModelDefinition.cs
View File

@ -7,7 +7,7 @@ namespace DeepTrace.Data
{
[BsonId]
public ObjectId? Id { get; set; }
public string Name { get; set; }
public byte[] Value { get; set; } //base64
public string Name { get; set; } = string.Empty;
public byte[] Value { get; set; } = Array.Empty<byte>(); //base64
}
}

2
DeepTrace/DeepTrace.csproj
View File

@ -6,6 +6,8 @@
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Blazor-ApexCharts" Version="0.9.21-beta" />
<PackageReference Include="CsvHelper" Version="30.0.1" />
<PackageReference Include="Microsoft.Extensions.Logging.Log4Net.AspNetCore" Version="6.1.0" />
<PackageReference Include="Microsoft.ML" Version="2.0.1" />
<PackageReference Include="Microsoft.ML.FastTree" Version="1.7.1" />
<PackageReference Include="Microsoft.ML.TimeSeries" Version="2.0.1" />

2
DeepTrace/ML/IMLProcessor.cs
View File

@ -5,7 +5,7 @@ namespace DeepTrace.ML;
public interface IMLProcessor
{
Task Train(ModelDefinition modelDef);
Task Train(ModelDefinition modelDef, Action<string> log);
byte[] Export();
void Import(byte[] data);
string Predict(DataSourceDefinition dataSource);

20
DeepTrace/ML/MLProcessor.cs
View File

@ -12,13 +12,21 @@ namespace DeepTrace.ML
private EstimatorBuilder _estimatorBuilder = new EstimatorBuilder();
private DataViewSchema? _schema;
private ITransformer? _transformer;
private static string _signature = "DeepTrace-Model-v1-" + typeof(MLProcessor).Name;
private readonly ILogger<MLProcessor> _logger;
public MLProcessor(ILogger<MLProcessor> logger)
{
_logger = logger;
}
private string Name { get; set; } = "TestModel";
public async Task Train(ModelDefinition modelDef)
public async Task Train(ModelDefinition modelDef, Action<string> log)
{
var pipeline = _estimatorBuilder.BuildPipeline(_mlContext, modelDef);
var (data, filename) = await MLHelpers.Convert(_mlContext, modelDef);
_mlContext.Log += (_,e) => LogEvents(log, e);
try
{
_schema = data.Schema;
@ -31,7 +39,15 @@ namespace DeepTrace.ML
}
private static string _signature = "DeepTrace-Model-v1-"+typeof(MLProcessor).Name;
private void LogEvents(Action<string> log, LoggingEventArgs e)
{
if(e.Kind.ToString() != "Trace")
{
_logger.LogDebug(e.Message);
log(e.Message);
}
}
public byte[] Export()
{

6
DeepTrace/ML/MedianHelper.cs
View File

@ -13,7 +13,7 @@ public static class MedianHelper
/// Pivot is selected ranodmly if random number generator is supplied else its selected as last element in the list.
/// Reference: Introduction to Algorithms 3rd Edition, Corman et al, pp 171
/// </summary>
private static int Partition<T>(this IList<T> list, int start, int end, Random rnd = null) where T : IComparable<T>
private static int Partition<T>(this IList<T> list, int start, int end, Random? rnd = null) where T : IComparable<T>
{
if (rnd != null)
list.Swap(end, rnd.Next(start, end + 1));
@ -34,11 +34,11 @@ public static class MedianHelper
/// Note: specified list would be mutated in the process.
/// Reference: Introduction to Algorithms 3rd Edition, Corman et al, pp 216
/// </summary>
public static T NthOrderStatistic<T>(this IList<T> list, int n, Random rnd = null) where T : IComparable<T>
public static T NthOrderStatistic<T>(this IList<T> list, int n, Random? rnd = null) where T : IComparable<T>
{
return NthOrderStatistic(list, n, 0, list.Count - 1, rnd);
}
private static T NthOrderStatistic<T>(this IList<T> list, int n, int start, int end, Random rnd) where T : IComparable<T>
private static T NthOrderStatistic<T>(this IList<T> list, int n, int start, int end, Random? rnd) where T : IComparable<T>
{
while (true)
{

7
DeepTrace/Pages/DataSources.razor
View File

@ -372,6 +372,9 @@
private void HandleTrain()
{
if ( DisplayData == null )
return;
var mlContext = new MLContext();
var dataView = mlContext.Data.LoadFromEnumerable<MyTimeSeries>(DisplayData.Series[0].Data.Select(x => new MyTimeSeries(Time: x.TimeStamp, Value: x.Value)));
@ -476,7 +479,7 @@
// -------- Spike detection tutorial ---------
private static void DetectSpike(MLContext mLContext, IDataView dataView, TimeSeries[]? data)
private static void DetectSpike(MLContext mLContext, IDataView dataView, TimeSeries[] data)
{
string outputColumnName = nameof(IidSpikePrediction.Prediction);
string inputColumnName = nameof(TimeSeriesDataTutorial.Value);
@ -531,7 +534,7 @@
class IidSpikePrediction
{
[VectorType(3)]
public double[] Prediction { get; set; }
public double[] Prediction { get; set; } = Array.Empty<double>();
}
}

136
DeepTrace/Pages/Training.razor
View File

@ -1,4 +1,5 @@
@page "/training"
@using CsvHelper;
@using DeepTrace.Data;
@using DeepTrace.ML;
@using DeepTrace.Services;
@ -7,6 +8,7 @@
@using Microsoft.ML;
@using PrometheusAPI;
@using System.Text;
@using System.Globalization;
@inject PrometheusClient Prometheus
@inject IDialogService DialogService
@ -16,6 +18,7 @@
@inject IEstimatorBuilder EstimatorBuilder
@inject NavigationManager NavManager
@inject IJSRuntime Js
@inject ILogger<MLProcessor> MLProcessorLogger
<PageTitle>Training</PageTitle>
@ -203,12 +206,12 @@
}
private ModelForm? _modelForm;
private TimeSeriesData? DisplayData { get; set; }
private List<DataSourceStorage> _dataSources = new();
private List<ModelDefinition> _modelDefinitions = new() {new()};
private DateTime? _minDate;
private DateTime? _maxDate;
private TimeSeriesData? DisplayData { get; set; }
private bool IsAddDisabled => DisplayData == null;
private DateTime? MinDate
@ -293,7 +296,7 @@
}
catch (Exception e)
{
ShowError(e.Message);
await ShowError(e.Message);
return;
}
@ -303,20 +306,20 @@
{
if (res.Status != StatusType.Success)
{
ShowError(res.Error ?? "Error");
await ShowError(res.Error ?? "Error");
return;
}
if (res.ResultType != ResultTypeType.Matrix)
{
ShowError($"Got {res.ResultType}, but Matrix expected for {def.Query}");
await ShowError($"Got {res.ResultType}, but Matrix expected for {def.Query}");
return;
}
var m = res.AsMatrix().Result;
if (m == null || m.Length != 1)
{
ShowError($"No data returned for {def.Query}");
await ShowError($"No data returned for {def.Query}");
return;
}
@ -335,12 +338,15 @@
private void HandleAddModel()
{
if (_modelForm == null)
return;
_modelDefinitions.Add(new());
_modelForm.CurrentModel = _modelDefinitions[^1];
StateHasChanged();
}
private void HandleDeleteModel()
private async Task HandleDeleteModel()
{
if (_modelDefinitions.Count < 2)
{
@ -350,7 +356,7 @@
var pos = _modelDefinitions.IndexOf(_modelForm!.CurrentModel);
if (pos < 0)
{
ShowError("Not found");
await ShowError("Not found");
return;
}
@ -360,10 +366,10 @@
if (toDelete.Id != null)
{
ModelService.Delete(toDelete);
await ModelService.Delete(toDelete);
}
StateHasChanged();
await InvokeAsync(StateHasChanged);
}
private async Task HandleAddTableContent()
@ -399,11 +405,14 @@
private void ItemHasBeenCommitted(object element)
{
Task.Run(async ()=>ModelService.Store(_modelForm!.CurrentModel));
Task.Run(() => ModelService.Store(_modelForm!.CurrentModel));
}
private async Task HandleRefresh()
{
if (DisplayData == null)
return;
var previousIntervals = _modelForm!.CurrentModel.IntervalDefinitionList;
foreach(var currentInterval in previousIntervals)
@ -415,20 +424,72 @@
// await InvokeAsync(StateHasChanged);
}
//Doesn't work
private class ImportedCsv
{
public DateTime Start { get; set; }
public DateTime End { get; set; }
public string Label { get; set; } = "";
}
private async Task HandleImport(IBrowserFile file)
{
var result = new StringBuilder();
var reader = new StreamReader(file.OpenReadStream(file.Size));
try
{
await HandleImportInternal(file);
}
catch (Exception e)
{
await ShowError($"Can't import: {e.Message}");
}
}
while (reader.Peek() >= 0)
result.AppendLine(await reader.ReadLineAsync());
private async Task HandleImportInternal(IBrowserFile file)
{
if ( _modelForm == null )
return;
result.ToString();
using var mem = new MemoryStream();
// https://stackoverflow.com/questions/67066860/blazorinputfile-synchronous-reads-are-not-supported
await file.OpenReadStream(file.Size).CopyToAsync(mem);
mem.Position = 0;
// var text = Encoding.UTF8.GetString(mem.ToArray());
using (var reader = new StreamReader(mem))
using (var csv = new CsvReader(reader, CultureInfo.InvariantCulture))
{
var records = csv.GetRecords<ImportedCsv>();
var yes = await YesNo("If you want to replace all intervals click Yes. Click No to append.");
if (yes == null)
return;
if (yes == true)
_modelForm.CurrentModel.IntervalDefinitionList.Clear();
var normalWorkStart = DateTime.MinValue;
foreach( var rec in records)
{
if(normalWorkStart != DateTime.MinValue)
{
var normalWorkEnd = rec.Start - TimeSpan.FromSeconds(1);
if(normalWorkStart<normalWorkEnd)
_modelForm.CurrentModel.IntervalDefinitionList.Add(new(normalWorkStart, normalWorkEnd, "Normal work"));
}
normalWorkStart = rec.End+TimeSpan.FromSeconds(1);
_modelForm.CurrentModel.IntervalDefinitionList.Add(new(rec.Start, rec.End, rec.Label));
}
}
await HandleRefresh();
await InvokeAsync(StateHasChanged);
}
private async Task HandleExport()
{
if (_modelForm == null)
return;
await Js.InvokeVoidAsync("open", $"{NavManager.BaseUri}api/download/mldata/{Uri.EscapeDataString(_modelForm.CurrentModel.Name)}", "_blank");
}
@ -440,7 +501,7 @@
await InvokeAsync(StateHasChanged);
}
private void ShowError(string text)
private async Task ShowError(string text)
{
var options = new DialogOptions
{
@ -449,19 +510,50 @@
var parameters = new DialogParameters();
parameters.Add("Text", text);
DialogService.Show<Controls.Dialog>("Error", parameters, options);
var d = DialogService.Show<Controls.Dialog>("Error", parameters, options);
await d.Result;
}
private async Task<bool?> YesNo(string text)
{
var options = new DialogOptions
{
CloseOnEscapeKey = true
};
var parameters = new DialogParameters();
parameters.Add(nameof(Controls.Dialog.Text), text);
parameters.Add(nameof(Controls.Dialog.IsYesNoCancel), true);
var d = DialogService.Show<Controls.Dialog>("Query", parameters, options);
var res = await d.Result;
return res?.Data as bool?;
}
private async Task HandleTrain()
{
var mlProcessor = new MLProcessor();
await mlProcessor.Train(_modelForm!.CurrentModel);
var mlProcessor = new MLProcessor(MLProcessorLogger);
MLProcessorLogger.LogInformation("Training started");
var options = new DialogOptions
{
CloseOnEscapeKey = true
};
var parameters = new DialogParameters();
parameters.Add(nameof(Controls.TrainingDialog.Text), _modelForm!.CurrentModel.Name);
parameters.Add(nameof(Controls.TrainingDialog.Processor), mlProcessor);
parameters.Add(nameof(Controls.TrainingDialog.Model), _modelForm.CurrentModel);
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
var trainedModel = new TrainedModelDefinition
{
Name = "TrainedModel",
Id = _modelForm!.CurrentModel.Id,
Name = _modelForm!.CurrentModel.Name,
Value = bytes
};
await TrainedModelService.Store(trainedModel);

10
DeepTrace/Program.cs
View File

@ -3,9 +3,19 @@ using PrometheusAPI;
using MongoDB.Driver;
using DeepTrace.Services;
using DeepTrace.ML;
using ApexCharts;
using log4net;
var builder = WebApplication.CreateBuilder(args);
builder.Services.AddLogging(logging =>
{
logging.ClearProviders();
GlobalContext.Properties["LOGS_ROOT"] = Environment.GetEnvironmentVariable("LOGS_ROOT") ?? "";
System.Text.Encoding.RegisterProvider(System.Text.CodePagesEncodingProvider.Instance);
logging.AddLog4Net("log4net.config");
});
// Add services to the container.
builder.Services.AddRazorPages();
builder.Services.AddServerSideBlazor();

4
DeepTrace/appsettings.Development.json
View File

@ -2,8 +2,8 @@
"DetailedErrors": true,
"Logging": {
"LogLevel": {
"Default": "Information",
"Microsoft.AspNetCore": "Warning"
"Default": "Trace",
"Microsoft.AspNetCore": "Information"
}
}
}

4
DeepTrace/appsettings.json
View File

@ -1,8 +1,8 @@
{
"Logging": {
"LogLevel": {
"Default": "Information",
"Microsoft.AspNetCore": "Warning"
"Default": "Trace",
"Microsoft.AspNetCore": "Information"
}
},
"AllowedHosts": "*",

63
DeepTrace/log4net.config Normal file
View File

@ -0,0 +1,63 @@
<?xml version="1.0" encoding="utf-8" ?>
<log4net>
<appender name="DebugAppender" type="log4net.Appender.DebugAppender" >
<layout type="log4net.Layout.PatternLayout">
<conversionPattern value="%date [%-2thread] %-5level %logger - %message%newline" />
</layout>
</appender>
<!--
<appender name="Console" type="log4net.Appender.ConsoleAppender">
<layout type="log4net.Layout.PatternLayout">
<conversionPattern value="%date [%-2thread] %-5level %-20logger - %message%newline" />
</layout>
</appender>
-->
<!--Console appender-->
<appender name="Console" type="log4net.Appender.ManagedColoredConsoleAppender">
<mapping>
<level value="INFO" />
<forecolor value="Green" />
</mapping>
<mapping>
<level value="WARN" />
<forecolor value="Yellow" />
</mapping>
<mapping>
<level value="ERROR" />
<forecolor value="Red" />
</mapping>
<mapping>
<level value="DEBUG" />
<forecolor value="Blue" />
</mapping>
<layout type="log4net.Layout.PatternLayout">
<conversionPattern value="%date{HH:mm:ss,fff} [%3thread] %-5level %-15logger{1} %message%newline" />
</layout>
</appender>
<appender name="RollingFile" type="log4net.Appender.RollingFileAppender">
<file value="log-file.txt" />
<appendToFile value="false" />
<layout type="log4net.Layout.PatternLayout">
<conversionPattern value="%date [%3thread] %-5level %logger [%property{NDC}] - %message%newline" />
</layout>
</appender>
<appender name="BufferingForwardingAppender" type="log4net.Appender.BufferingForwardingAppender" >
<bufferSize value="1"/>
<appender-ref ref="DebugAppender" />
<appender-ref ref="Console" />
<appender-ref ref="RollingFile" />
</appender>
<logger name="System.Net.Http">
<level value="ERROR"/>
</logger>
<root>
<level value="ALL"/>
<appender-ref ref="BufferingForwardingAppender" />
</root>
</log4net>