public RlmOptimizer(IRlmDbData rlmDbData, IRlmRneuronProcessor gpu = null)
        {
            Resources          = new Dictionary <string, Resource>();
            ResourceAttributes = new Dictionary <string, ResourceAttribute>();
            Constraints        = new Dictionary <string, Constraint>();
            CycleOutputs       = new Dictionary <string, object>();
            SessionOutputs     = new Dictionary <string, List <object> >();
            CycleInputs        = new Dictionary <string, object>();

            TrainingVariables.Add("CycleScore", new TrainingVariable()
            {
                Name = "CycleScore"
            });
            TrainingVariables.Add("SessionScore", new TrainingVariable()
            {
                Name = "SessionScore"
            });

            //if (!string.IsNullOrEmpty(databaseName))
            //{
            //    DatabaseName = databaseName;
            //}

            RlmDbData    = rlmDbData;
            DatabaseName = rlmDbData.DatabaseName;

            if (gpu != null)
            {
                Gpu = gpu;
            }
        }
Exemple #2
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        private void btnVisualizer_Click(object sender, RoutedEventArgs e)
        {
            //rlmDbData = new RlmDbDataPostgreSqlServer(dbIdentifier);
            rlmDbData = new RlmDbDataSQLServer(dbIdentifier);
            core      = new RLVCore(rlmDbData);

            rlvPanel = new VisualizerWindow(core, challenger.HighestMoveCount, challenger.RecentMoves);
            rlvPanel.Show();
        }
 /// <summary>
 /// sets your preferred database name
 /// </summary>
 /// <param name="databaseName">Uses a custom database name instead of the default generated name</param>
 /// <param name="persistData">Allows you to turn on/off the data persistence feature of the RLM. Turned on by default.</param>
 public RlmNetwork(IRlmDbData rlmDbData, bool persistData = true, IRlmRneuronProcessor gpu = null)
 {
     PersistData    = persistData;
     this.RlmDBData = rlmDbData;
     DatabaseName   = rlmDbData.DatabaseName;
     rlmDbData.Initialize();
     SessionCaseHistory = new RlmSessionCaseHistory(rlmDbData);
     Initialize(gpu);
 }
Exemple #4
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        private void Window_Loaded(object sender, RoutedEventArgs e)
        {
            string dbIdentifier = "RLV_small";

            // instantiate visualizer with this window as its parent reference
            visualizer = new RLVOutputVisualizer(this);
            rlmDbData  = new RlmDbDataSQLServer(dbIdentifier);
            //rlmDbData = new RlmDbDataPostgreSqlServer(dbIdentifier);
            core = new RLVCore(rlmDbData);

            this.Top = 20;
            rlvPanel = new VisualizerWindow(core, visualizer);
        }
Exemple #5
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        private void startOptimizing()
        {
            trainingOverlay.Visibility = Visibility.Visible;
            selectedSlotIndex          = -1;
            _row    = -1;
            _col    = -1;
            itemRow = -1;
            itemCol = 1;

            SimulationPanel simPanel = new SimulationPanel(mock);

            simPanel.SetSimSettings(simSettings);
            //bool? result = simPanel.ShowDialog();

            simPanel.btnRun_Click(null, null);

            //if (result.HasValue && result.Value == true)
            {
                // resets grid to default
                FillGrid(gridIceCreamShelves, Colors.LightGray);
                EnableControlButtons(false);

                // set simulation settings
                simSettings.SimType                = simPanel.SimType;
                simSettings.Sessions               = simPanel.Sessions;
                simSettings.Hours                  = simPanel.Hours;
                simSettings.Score                  = simPanel.Score;
                simSettings.EnableSimDisplay       = simPanel.EnableSimDisplay;
                simSettings.DefaultScorePercentage = simPanel.simScoreSlider.Value;

                txtTargetScore.Text = "";
                if (simSettings.SimType == SimulationType.Score)
                {
                    txtTargetScore.Text = simSettings.Score.Value.ToString("n");
                }
                else
                {
                    txtTargetScore.Visibility = Visibility.Hidden;
                }

                //if (simSettings.SimType == SimulationType.Sessions)
                //{
                //    lblSessionPerBatch.Visibility = Visibility.Hidden;
                //    txtSessionPerBatch.Visibility = Visibility.Hidden;
                //}
                //else
                //{
                //    lblSessionPerBatch.Visibility = Visibility.Visible;
                //    txtSessionPerBatch.Visibility = Visibility.Visible;
                //}


                string dbIdentifier = "RLM_planogram_" + Guid.NewGuid().ToString("N");
                // instantiate visualizer with this window as its parent reference
                visualizer = new RLVOutputVisualizer(this);
                rlmDbData  = new RlmDbDataSQLServer(dbIdentifier);
                //rlmDbData = new RlmDbDataPostgreSqlServer(dbIdentifier);
                core = new RLVCore(rlmDbData);

                // open temporary RLV container panel
                // todo this must be embeded in this Window instead of the temporary container
                if (rlvPanel != null)
                {
                    rlvPanel.Close();
                }

                rlvPanel = new VisualizerWindow(core, visualizer);
                Task.Run(() =>
                {
                    // get items from db as well as the min and max metric scores as we need that for the calculation later on
                    Item[] items;
                    //using (PlanogramContext ctx = new PlanogramContext())
                    {
                        //MockData mock = new MockData(ctx);
                        items = itemsCache = mock.GetItemsWithAttr();
                        simSettings.ItemMetricMin = mock.GetItemMinimumScore(simSettings);
                        simSettings.ItemMetricMax = mock.GetItemMaximumScore(simSettings);
                    }

                    // initialize and start RLM training
                    optimizer = new PlanogramOptimizer(items, simSettings, this.UpdateRLMResults, this.UpdateRLMStatus, Logger, dbIdentifier, OnRLMDataPersistProgress);
                    //optimizer.OnSessionDone += Optimizer_OnSessionDone;
                    optimizer.StartOptimization();
                });
            }
        }
Exemple #6
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 public RlmNetworkLegacy(IRlmDbData rlmDbData, bool persistData = true) : base(rlmDbData, persistData)
 {
     rlmDbDataLegacy = rlmDbData;
 }
 public RlmNetworkWebAPI(IRlmDbData rlmDbData) : base(rlmDbData)
 {
 }
Exemple #8
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 public RlmSessionCaseHistory(IRlmDbData rlmDb)
 {
     this.rlmDb = rlmDb;
     rlmDb.Initialize();
     DatabaseName = rlmDb.DatabaseName;
 }
Exemple #9
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 public RLVCore(IRlmDbData rlmDb)
 {
     rlmDb.Initialize();
     rlmHistory = new RlmSessionCaseHistory(rlmDb);
 }
Exemple #10
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        private void runSlmBtn_Click(object sender, RoutedEventArgs e)
        {
            selectedSlotIndex = -1;
            _row    = -1;
            _col    = -1;
            itemRow = -1;
            itemCol = -1;

            SimulationPanel simPanel = new SimulationPanel();

            simPanel.SetSimSettings(simSettings);
            bool?result = simPanel.ShowDialog();

            if (result.HasValue && result.Value == true)
            {
                // resets grid to default
                usePerfColor = false;
                FillGrid(planogram, Colors.LightGray);
                if (headToHead)
                {
                    FillGrid(planogramTensorflow, Colors.LightGray);
                }

                // disable control buttons
                //statusTxt.Text = statusTxtTensor.Text = "";
                statusTxtTensor.Text = "Waiting for RLM to finish running...";
                EnableControlButtons(false);

                // set simulation settings
                simSettings.SimType                = simPanel.SimType;
                simSettings.Sessions               = simPanel.Sessions;
                simSettings.Hours                  = simPanel.Hours;
                simSettings.Score                  = simPanel.Score;
                simSettings.EnableSimDisplay       = simPanel.EnableSimDisplay;
                simSettings.DefaultScorePercentage = simPanel.simScoreSlider.Value;
                simSettings.HiddenLayers           = simPanel.HiddenLayers;
                simSettings.HiddenLayerNeurons     = simPanel.HiddenLayerNeurons;

                targetScoreTxt.Text = "";
                if (simSettings.SimType == SimulationType.Score)
                {
                    targetScoreLbl.Visibility  = Visibility.Visible;
                    targetScoreTxt.Visibility  = Visibility.Visible;
                    targetScoreTxt.Text        = simSettings.Score.Value.ToString("n");
                    targetScoreTxt2.Visibility = Visibility.Visible;
                    targetScoreTxt2.Text       = simSettings.Score.Value.ToString("n");
                }
                else
                {
                    targetScoreLbl.Visibility  = Visibility.Hidden;
                    targetScoreTxt.Visibility  = Visibility.Hidden;
                    targetScoreTxt2.Visibility = Visibility.Hidden;
                }

                if (simSettings.SimType == SimulationType.Sessions)
                {
                    sessionPerBatchLbl.Visibility = Visibility.Hidden;
                    sessionPerBatchTxt.Visibility = Visibility.Hidden;
                }
                else
                {
                    sessionPerBatchLbl.Visibility = Visibility.Visible;
                    sessionPerBatchTxt.Visibility = Visibility.Visible;
                }

                Logger.Clear();


                string dbIdentifier = "RLM_planogram_" + Guid.NewGuid().ToString("N");
                // instantiate visualizer with this window as its parent reference
                visualizer = new RLVOutputVisualizer(this);
                rlmDbData  = new RlmDbDataSQLServer(dbIdentifier);
                //rlmDbData = new RlmDbDataPostgreSqlServer(dbIdentifier);
                core = new RLVCore(rlmDbData);

                // subscribe mainwindow to the comparison event
                //visualizer.LearningComparisonDisplayResultsEvent += DisplayLearningComparisonResults;

                // open temporary RLV container panel
                // todo this must be embeded in this Window instead of the temporary container
                if (rlvPanel != null)
                {
                    rlvPanel.Close();
                }

                rlvPanel = new TempRLVContainerPanel(core, visualizer);

                //this.Top = 20;
                //tmpPanel.Top = this.Top;
                //this.Height = tmpPanel.Height;
                //tmpPanel.Left = 10;
                //this.Left = tmpPanel.Width + tmpPanel.Left;
                //tmpPanel.Visibility = Visibility.Hidden;

                Task.Run(() =>
                {
                    // get items from db as well as the min and max metric scores as we need that for the calculation later on
                    Item[] items;
                    using (PlanogramContext ctx = new PlanogramContext())
                    {
                        MockData mock             = new MockData(ctx);
                        items                     = itemsCache = mock.GetItemsWithAttr();
                        simSettings.ItemMetricMin = mock.GetItemMinimumScore(simSettings);
                        simSettings.ItemMetricMax = mock.GetItemMaximumScore(simSettings);
                    }

                    // let's tensorflow (or other listeners) know that it should start training
                    //OnSimulationStart?.Invoke(items, simSettings, tokenSource.Token); return;

                    // initialize and start RLM training
                    optimizer = new PlanogramOptimizer(items, simSettings, this.UpdateRLMResults, this.UpdateRLMStatus, Logger, dbIdentifier);
                    //optimizer.OnSessionDone += Optimizer_OnSessionDone;
                    optimizer.StartOptimization(tokenSource.Token);
                });
            }
        }