From 9bb198e0ee2574684a3f854285b7fe0f0609eeab Mon Sep 17 00:00:00 2001 From: Joseph Wee Date: Fri, 25 Feb 2022 09:50:58 +0800 Subject: [PATCH] Revised the classification ML model Added MLModel2 --- TicTacToeML/MLModel2.consumption.cs | 91 + TicTacToeML/MLModel2.mbconfig | 6080 +++++++++++++++++ TicTacToeML/MLModel2.training.cs | 41 + TicTacToeML/MLModel2.zip | Bin 0 -> 52726 bytes .../MLModel2.consumption.cs | 91 + .../MLNET_Consumption_Model/MLModel2.cs | 34 + TicTacToeML/TicTacToeML.csproj | 15 + WebApp/Controllers/TicTacToeController.cs | 28 +- WebApp/Global.asax.cs | 10 +- WebApp/LocalDB/TicTacToeData.mdf | Bin 8388608 -> 8388608 bytes WebApp/LocalDB/TicTacToeData_log.ldf | Bin 8388608 -> 8388608 bytes WebApp/MLModel2.zip | Bin 0 -> 52726 bytes WebApp/Web.config | 2 +- WebApp/WebApp.csproj | 1 + 14 files changed, 6385 insertions(+), 8 deletions(-) create mode 100644 TicTacToeML/MLModel2.consumption.cs create mode 100644 TicTacToeML/MLModel2.mbconfig create mode 100644 TicTacToeML/MLModel2.training.cs create mode 100644 TicTacToeML/MLModel2.zip create mode 100644 TicTacToeML/MLNET_Consumption_Model/MLModel2.consumption.cs create mode 100644 TicTacToeML/MLNET_Consumption_Model/MLModel2.cs create mode 100644 WebApp/MLModel2.zip diff --git a/TicTacToeML/MLModel2.consumption.cs b/TicTacToeML/MLModel2.consumption.cs new file mode 100644 index 0000000..587856c --- /dev/null +++ b/TicTacToeML/MLModel2.consumption.cs @@ -0,0 +1,91 @@ +// This file was auto-generated by ML.NET Model Builder. +using Microsoft.ML; +using Microsoft.ML.Data; +using System; +using System.Linq; +using System.IO; +using System.Collections.Generic; +namespace TicTacToeML +{ + public partial class MLModel2 + { + /// + /// model input class for MLModel2. + /// + #region model input class + public class ModelInput + { + [ColumnName(@"MoveNumber")] + public float MoveNumber { get; set; } + + [ColumnName(@"Cell0")] + public float Cell0 { get; set; } + + [ColumnName(@"Cell1")] + public float Cell1 { get; set; } + + [ColumnName(@"Cell2")] + public float Cell2 { get; set; } + + [ColumnName(@"Cell3")] + public float Cell3 { get; set; } + + [ColumnName(@"Cell4")] + public float Cell4 { get; set; } + + [ColumnName(@"Cell5")] + public float Cell5 { get; set; } + + [ColumnName(@"Cell6")] + public float Cell6 { get; set; } + + [ColumnName(@"Cell7")] + public float Cell7 { get; set; } + + [ColumnName(@"Cell8")] + public float Cell8 { get; set; } + + [ColumnName(@"GameResultCode")] + public float GameResultCode { get; set; } + + } + + #endregion + + /// + /// model output class for MLModel2. + /// + #region model output class + public class ModelOutput + { + [ColumnName("PredictedLabel")] + public float Prediction { get; set; } + + public float[] Score { get; set; } + } + + #endregion + + private static string MLNetModelPath = Path.GetFullPath("MLModel2.zip"); + + public static readonly Lazy> PredictEngine = new Lazy>(() => CreatePredictEngine(), true); + + /// + /// Use this method to predict on . + /// + /// model input. + /// + public static ModelOutput Predict(ModelInput input) + { + var predEngine = PredictEngine.Value; + return predEngine.Predict(input); + } + + private static PredictionEngine CreatePredictEngine() + { + var mlContext = new MLContext(); + ITransformer mlModel = mlContext.Model.Load(MLNetModelPath, out var _); + return mlContext.Model.CreatePredictionEngine(mlModel); + } + } +} diff --git a/TicTacToeML/MLModel2.mbconfig b/TicTacToeML/MLModel2.mbconfig new file mode 100644 index 0000000..7ffa9fe --- /dev/null +++ b/TicTacToeML/MLModel2.mbconfig @@ -0,0 +1,6080 @@ +{ + "TrainingTime": 600, + "Scenario": "Classification", + "DataSource": { + "Type": "TabularFile", + "Version": 1, + "FilePath": "C:\\Users\\Zhiyong\\source\\repos\\Tic-Tac-Toe\\TicTacToeML\\MLNET_TrainingData\\ClassificationModel01Data-2022-02-23-1414.csv", + "Delimiter": ",", + "DecimalMarker": ".", + "HasHeader": true, + "ColumnProperties": [ + { + "ColumnName": 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"[{\"EstimatorType\":\"ReplaceMissingValues\",\"Inputs\":[\"Cell0\",\"Cell1\",\"Cell2\",\"Cell3\",\"Cell4\",\"Cell5\",\"Cell6\",\"Cell7\",\"Cell8\"],\"Outputs\":[\"Cell0\",\"Cell1\",\"Cell2\",\"Cell3\",\"Cell4\",\"Cell5\",\"Cell6\",\"Cell7\",\"Cell8\"]},{\"EstimatorType\":\"Concatenate\",\"Inputs\":[\"Cell0\",\"Cell1\",\"Cell2\",\"Cell3\",\"Cell4\",\"Cell5\",\"Cell6\",\"Cell7\",\"Cell8\"],\"Outputs\":[\"Features\"]},{\"EstimatorType\":\"MapValueToKey\",\"Inputs\":[\"GameResultCode\"],\"Outputs\":[\"GameResultCode\"]},{\"LabelColumnName\":\"GameResultCode\",\"FeatureColumnName\":\"Features\",\"NumberOfLeaves\":\"441\",\"MinimumExampleCountPerLeaf\":\"110\",\"NumberOfTrees\":\"1110\",\"LearningRate\":\"1\",\"FeatureFraction\":\"0.695694987358897\",\"MaximumBinCountPerFeature\":\"8\",\"EstimatorType\":\"FastTreeOva\",\"Inputs\":[\"GameResultCode\"],\"Outputs\":[\"Features\"]},{\"EstimatorType\":\"MapKeyToValue\",\"Inputs\":[\"PredictedLabel\"],\"Outputs\":[\"PredictedLabel\"]}]", + "MetricName": "MicroAccuracy" + }, + "Type": "TrainingConfig", + "Version": 1 +} \ No newline at end of file diff --git a/TicTacToeML/MLModel2.training.cs b/TicTacToeML/MLModel2.training.cs new file mode 100644 index 0000000..4f74085 --- /dev/null +++ b/TicTacToeML/MLModel2.training.cs @@ -0,0 +1,41 @@ +// This file was auto-generated by ML.NET Model Builder. +using System; +using System.Collections.Generic; +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; + +namespace TicTacToeML +{ + public partial class MLModel2 + { + public static ITransformer RetrainPipeline(MLContext context, IDataView trainData) + { + var pipeline = BuildPipeline(context); + var model = pipeline.Fit(trainData); + + return model; + } + + /// + /// build the pipeline that is used from model builder. Use this function to retrain model. + /// + /// + /// + public static IEstimator BuildPipeline(MLContext mlContext) + { + // Data process configuration with pipeline data transformations + var pipeline = mlContext.Transforms.ReplaceMissingValues(new []{new InputOutputColumnPair(@"Cell0", @"Cell0"),new InputOutputColumnPair(@"Cell1", @"Cell1"),new InputOutputColumnPair(@"Cell2", @"Cell2"),new InputOutputColumnPair(@"Cell3", @"Cell3"),new InputOutputColumnPair(@"Cell4", @"Cell4"),new InputOutputColumnPair(@"Cell5", @"Cell5"),new InputOutputColumnPair(@"Cell6", @"Cell6"),new InputOutputColumnPair(@"Cell7", @"Cell7"),new InputOutputColumnPair(@"Cell8", @"Cell8")}) + .Append(mlContext.Transforms.Concatenate(@"Features", new []{@"Cell0",@"Cell1",@"Cell2",@"Cell3",@"Cell4",@"Cell5",@"Cell6",@"Cell7",@"Cell8"})) + .Append(mlContext.Transforms.Conversion.MapValueToKey(@"GameResultCode", @"GameResultCode")) + 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partial class MLModel2 + { + /// + /// model input class for MLModel2. + /// + #region model input class + public class ModelInput + { + [ColumnName(@"MoveNumber")] + public float MoveNumber { get; set; } + + [ColumnName(@"Cell0")] + public float Cell0 { get; set; } + + [ColumnName(@"Cell1")] + public float Cell1 { get; set; } + + [ColumnName(@"Cell2")] + public float Cell2 { get; set; } + + [ColumnName(@"Cell3")] + public float Cell3 { get; set; } + + [ColumnName(@"Cell4")] + public float Cell4 { get; set; } + + [ColumnName(@"Cell5")] + public float Cell5 { get; set; } + + [ColumnName(@"Cell6")] + public float Cell6 { get; set; } + + [ColumnName(@"Cell7")] + public float Cell7 { get; set; } + + [ColumnName(@"Cell8")] + public float Cell8 { get; set; } + + [ColumnName(@"GameResultCode")] + public float GameResultCode { get; set; } + + } + + #endregion + + /// + /// model output class for MLModel2. + /// + #region model output class + public class ModelOutput + { + [ColumnName("PredictedLabel")] + public float Prediction { get; set; } + + public float[] Score { get; set; } + } + + #endregion + + private static string MLNetModelPath = Path.GetFullPath("MLModel2.zip"); + + public static readonly Lazy> PredictEngine = new Lazy>(() => CreatePredictEngine(), true); + + /// + /// Use this method to predict on . + /// + /// model input. + /// + public static ModelOutput Predict(ModelInput input) + { + var predEngine = PredictEngine.Value; + return predEngine.Predict(input); + } + + private static PredictionEngine CreatePredictEngine() + { + var mlContext = new MLContext(); + ITransformer mlModel = mlContext.Model.Load(MLNetModelPath, out var _); + return mlContext.Model.CreatePredictionEngine(mlModel); + } + } +} diff --git a/TicTacToeML/MLNET_Consumption_Model/MLModel2.cs b/TicTacToeML/MLNET_Consumption_Model/MLModel2.cs new file mode 100644 index 0000000..5a37ebb --- /dev/null +++ b/TicTacToeML/MLNET_Consumption_Model/MLModel2.cs @@ -0,0 +1,34 @@ +using System; +using System.Collections.Generic; +using System.IO; +using System.Linq; +using System.Text; +using System.Threading.Tasks; + +namespace TicTacToe.ML +{ + public partial class MLModel2 + { + public static bool SetMLNetModelPath(string MLModelPath) + { + if (!File.Exists(MLModelPath)) + return false; + + FileInfo fileInfo = new FileInfo(MLModelPath); + if (fileInfo.Extension != ".zip") + return false; + + MLNetModelPath = MLModelPath; + + return true; + } + + public static ModelOutput Predict(ModelInput input, string MLModelPath) + { + if (SetMLNetModelPath(MLModelPath)) + return Predict(input); + else + throw new FileNotFoundException("Unable to find MLNETModel"); + } + } +} diff --git a/TicTacToeML/TicTacToeML.csproj b/TicTacToeML/TicTacToeML.csproj index e6a3c18..431fddf 100644 --- a/TicTacToeML/TicTacToeML.csproj +++ b/TicTacToeML/TicTacToeML.csproj @@ -110,6 +110,8 @@ + + @@ -124,6 +126,7 @@ + @@ -138,6 +141,18 @@ PreserveNewest + + + MLModel2.mbconfig + + + MLModel2.mbconfig + + + MLModel2.mbconfig + PreserveNewest + + diff --git a/WebApp/Controllers/TicTacToeController.cs b/WebApp/Controllers/TicTacToeController.cs index 0073e52..3431ac2 100644 --- a/WebApp/Controllers/TicTacToeController.cs +++ b/WebApp/Controllers/TicTacToeController.cs @@ -60,10 +60,25 @@ public IHttpActionResult Post([FromBody] TicTacToe.Models.TicTacToeUpdateRequest cellStates[tttUpdateResponse.ComputerMove.Value] = 2; } - var inputModel = - new MLModel1.ModelInput() + //var inputModel1 = + // new MLModel1.ModelInput() + // { + // MoveNumber = moveNumber, + // Cell0 = value.CellStates[0], + // Cell1 = value.CellStates[1], + // Cell2 = value.CellStates[2], + // Cell3 = value.CellStates[3], + // Cell4 = value.CellStates[4], + // Cell5 = value.CellStates[5], + // Cell6 = value.CellStates[6], + // Cell7 = value.CellStates[7], + // Cell8 = value.CellStates[8], + // GameResultCode = 0 + // }; + + var inputModel2 = + new MLModel2.ModelInput() { - MoveNumber = moveNumber, Cell0 = value.CellStates[0], Cell1 = value.CellStates[1], Cell2 = value.CellStates[2], @@ -77,10 +92,11 @@ public IHttpActionResult Post([FromBody] TicTacToe.Models.TicTacToeUpdateRequest }; //Get Prediction - var prediction = MLModel1.Predict(inputModel); + //var prediction1 = MLModel1.Predict(inputModel1); + var prediction2 = MLModel2.Predict(inputModel2); - tttUpdateResponse.Prediction = prediction.Prediction; - tttUpdateResponse.PredictionScore = prediction.Score; + tttUpdateResponse.Prediction = prediction2.Prediction; + tttUpdateResponse.PredictionScore = prediction2.Score; } } } diff --git a/WebApp/Global.asax.cs b/WebApp/Global.asax.cs index 9920334..285ceba 100644 --- a/WebApp/Global.asax.cs +++ b/WebApp/Global.asax.cs @@ -1,5 +1,6 @@ using System; using System.Collections.Generic; +using System.IO; using System.Linq; using System.Web; using System.Web.Http; @@ -22,7 +23,14 @@ protected void Application_Start() string MLNetModelPath = System.Configuration.ConfigurationManager.AppSettings["MLNetModelPath"]; - TicTacToe.ML.MLModel1.SetMLNetModelPath(MLNetModelPath); + + TicTacToe.ML.MLModel1.SetMLNetModelPath( + Path.Combine(MLNetModelPath, "MLModel1.zip") + ); + + TicTacToe.ML.MLModel2.SetMLNetModelPath( + Path.Combine(MLNetModelPath, "MLModel2.zip") + ); } } } diff --git a/WebApp/LocalDB/TicTacToeData.mdf b/WebApp/LocalDB/TicTacToeData.mdf index 58c7dab6a7137a6381db35a3ced78fc8444cf1ed..c0464c5f4a44a104a911e01e9618cecf0fba49e5 100644 GIT binary patch delta 57249 zcmZ|Y37l2qAII@KY0|W>npRUnQEJ+gr9rZl1|hUegt9dVA>D~?c1AL?)z~UzOUAAc zLWq+7mdYNYP}cH)&b{M)f1ls$b$A_y-aY5s=brBUeV^w!=OmNKn#r&|-ld?~`r3&^ zZbE;xPE~Z8xpY~FMPmyNs4;U)`+AG!b~vW(%pC{r({yuibtMzeHtbkY@@=!G<-;1y z96NA)&W=SZ2kyS>%=H6v7i}BeXH2umH!^b4BULrFAZJug`$plH>m+IzkVte5|CRawiNs?wHnh(PTaB>o6tPur&-@qpA(<8z1>nv#7o3FrKM?g^yhK%bai+1yy6# zH*VLi@rLRHSXce;4Kr@q(Ku{Ps&3lR^zQcQ-yR+0f4}{hmmfGO^V&x{91K( z3cn}X!mqSz5q@Q#3u;yWO3mYO_nT_(mF5-gTISb|TIqgt?N$}ZX8Cn0hMrlY 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