features and labels calculated

Projects/Superalgos/TS/Bot-Modules/Learning-Bot/Low-Frequency-Learning/LearningSystem.js

@@ -280,7 +280,7 @@ exports.newSuperalgosBotModulesLearningSystem = function (processIndex) {
         }
 
         /* Here we check if there is a formula to be evaluated */
-        if ((node.type === 'Formula' || node.type === 'Announcement Formula') && evaluating === 'Formulas') {
+        if ((node.type === 'Feature Formula' || node.type === 'Label Formula') && evaluating === 'Formulas') {
             if (node.code !== undefined) {
                 /* We will eval this formula */
                 if (isDescendent === true) {
@@ -405,7 +405,7 @@ exports.newSuperalgosBotModulesLearningSystem = function (processIndex) {
             return
         } else {
             if (value !== undefined) {
-                if (node.type === 'Formula' && isNaN(value)) {
+                if ((node.type === 'Feature Formula' || node.type === 'Label Formula') && isNaN(value)) {
 
                     docs = {
                         project: 'Superalgos',

Projects/Superalgos/UI/Function-Libraries/DependenciesFilter.js

@@ -43,7 +43,7 @@ function newSuperalgosFunctionLibraryDependenciesFilter() {
         return filters
 
         function recursiveFilter(node) {
-            if (node.type === 'Javascript Code' || node.type === 'Formula' || node.type === 'Feature Formula') {
+            if (node.type === 'Javascript Code' || node.type === 'Formula' || node.type === 'Feature Formula' || node.type === 'Data Formula') {
                 filter(node.code)
             }
 

Projects/Superalgos/UI/Function-Libraries/LearningSessionFunctions.js

@@ -72,7 +72,8 @@ function newSuperalgosFunctionLibraryLearningSessionFunctions() {
             'Layers API->Code API->' +
             'Secuential Model->Functional Model->' + 
             'Input Layer->Secuential Layer->Output Layer->'+
-            'Input Shape->Batch Input Shape->Input Features->Feature->Feature Formula->' + 
+            'Input Shape->Batch Input Shape->Input Features->Data Feature->Feature Formula->' + 
+            'Output Labels->Data Label->Label Formula->' + 
             'Advanced Activation Layers->Basic Layers->Convolutional Layers->' +
             'Conv 1D Layer->Conv 2D Layer->Conv 2D Transpose Layer->Conv 3D Layer->Cropping 2D Layer->Depthwise Convo 2D Layer->Separable Convo 2D Layer->Up Sampling 2D Layer->' +
             'Activation Layer->Dense Layer->Dropout Layer->Embedding Layer->Flatten Layer->Permutable Layer->Rrepeat Vector Layer->Reshape Layer->Spatial Dropout 1D Layer->' +

Projects/TensorFlow/Schemas/AppSchema.json

@@ -2915,9 +2915,9 @@
             {
                 "action": "Add UI Object",
                 "disableIfPropertyIsDefined": true,
-                "propertyToCheckFor": "dataLabelFormula",
-                "label": "Add Data Label Formula",
-                "relatedUiObject": "Data Label Formula",
+                "propertyToCheckFor": "labelFormula",
+                "label": "Add Label Formula",
+                "relatedUiObject": "Label Formula",
                 "actionFunction": "payload.executeAction"
             },
             {
@@ -2938,16 +2938,16 @@
         "propertyNameAtParent": "dataLabels",
         "childrenNodesProperties": [
             {
-                "name": "dataLabelFormula",
+                "name": "labelFormula",
                 "type": "node",
-                "childType": "Data Label Formula",
+                "childType": "Label Formula",
                 "autoAdd": true
             }
         ],
         "icon": "tensorflow"
     },
     {
-        "type": "Data Label Formula",
+        "type": "Label Formula",
         "menuItems": [
             {
                 "action": "Edit",
@@ -2977,7 +2977,7 @@
         "attachingRules": {
             "compatibleTypes": "->Data Label->"
         },
-        "propertyNameAtParent": "dataLabelFormula",
+        "propertyNameAtParent": "labelFormula",
         "childrenNodesProperties": [],
         "icon": "tensorflow"
     },

Projects/TensorFlow/TS/Bot-Modules/Learning-Bot/Low-Frequency-Learning/TensorFlowLibrary.js

@@ -25,6 +25,9 @@ exports.newTensorFlowBotModulesTensorFlowLibrary = function (processIndex) {
     let tensorFlowBackend
     let tensorFlowAPI
     let tensorFlowModel
+    let tensorFlowData
+    let features = []
+    let labels = []
 
     return thisObject
 
@@ -279,6 +282,14 @@ exports.newTensorFlowBotModulesTensorFlowLibrary = function (processIndex) {
         chart = undefined
         exchange = undefined
         market = undefined
+
+        tensorFlowBackend = undefined
+        tensorFlowAPI = undefined
+        tensorFlowModel = undefined
+        tensorFlowData = undefined
+
+        features = []
+        labels = []
     }
 
     function updateChart(pChart, pExchange, pMarket) {
@@ -299,14 +310,60 @@ exports.newTensorFlowBotModulesTensorFlowLibrary = function (processIndex) {
     }
 
     function run(callbackFunction) {
-        /*
-        Do your magic here...
-        */
+
+        let layersModel = learningSystem.machineLearningLibrary.typeOfLearning.typeOfModel.model.api.layersModel
 
         /*
-        if all is good, return this...
+        Building the Features Tensor
         */
-        callbackFunction(TS.projects.superalgos.globals.standardResponses.DEFAULT_OK_RESPONSE)
+        if (layersModel.inputLayer === undefined) {
+            // TODO
+        }
+        if (layersModel.inputLayer.inputFeatures === undefined) {
+            // TODO
+        }
+        learningSystem.evalFormulas(layersModel.inputLayer.inputFeatures, layersModel.inputLayer.inputFeatures.type)
+
+        for (let i = 0; i < layersModel.inputLayer.inputFeatures.dataFeatures.length; i++) {
+            let dataFeature = layersModel.inputLayer.inputFeatures.dataFeatures[i]
+            if (dataFeature.featureFormula === undefined) { continue }
+            let featureValue = learningSystem.formulas.get(dataFeature.featureFormula.id)
+            features.push(featureValue)
+        }
+
+        /*
+        Building the Labels Tensor
+        */
+        if (layersModel.outputLayer === undefined) {
+            // TODO
+        }
+        if (layersModel.outputLayer.outputLabels === undefined) {
+            // TODO
+        }
+        learningSystem.evalFormulas(layersModel.outputLayer.outputLabels, layersModel.outputLayer.outputLabels.type)
+
+        for (let i = 0; i < layersModel.outputLayer.outputLabels.dataLabels.length; i++) {
+            let dataLabel = layersModel.outputLayer.outputLabels.dataLabels[i]
+            if (dataLabel.labelFormula === undefined) { continue }
+            let labelValue = learningSystem.formulas.get(dataLabel.labelFormula.id)
+            labels.push(labelValue)
+        }
+
+        tensorFlowData = require("@tensorflow/tfjs-data")
+
+        let dataset = tensorFlowData.array([features, labels])
+
+        tensorFlowModel.fitDataset(dataset, { epochs: 5 }).then(info => {
+            console.log('Accuracy', info.history.acc);
+
+            /*
+            if all is good, return this...
+            */
+            callbackFunction(TS.projects.superalgos.globals.standardResponses.DEFAULT_OK_RESPONSE)
+
+        });
+
+
 
         /*
         if something is bad, return this...