From 6f798869049aee68cf84f381317cc1ee46dbcce2 Mon Sep 17 00:00:00 2001 From: TAMARA JERINIC Date: Thu, 5 May 2022 00:05:27 +0200 Subject: Promenjena lokacija columnType parametra. --- backend/microservice/api/newmlservice.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) (limited to 'backend/microservice/api') diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index d84d9567..826ac7cb 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -180,17 +180,20 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): kategorijskekolone=[] ###PRETVARANJE NUMERICKIH U KATREGORIJSKE AKO JE KORISNIK TAKO OZNACIO columnInfo=paramsDataset['columnInfo'] - for col in columnInfo: - if(col['columnType']=="Kategorijski"): + columnTypes=paramsExperiment['columnTypes'] + for i in range(len(columnInfo)): + col=columnInfo[i] + if(columnTypes[i]=="categorical"): data[col['columnName']]=data[col['columnName']].apply(str) kategorijskekolone.append(col['coumnName']) - + #kategorijskekolone=data.select_dtypes(include=['object']).columns + print(kategorijskekolone) ###NULL null_value_options = paramsExperiment["nullValues"] null_values_replacers = paramsExperiment["nullValuesReplacers"] if(null_value_options=='replace'): - #print("replace null") # + #print("replace null") dict=null_values_replacers while(len(dict)>0): replace=dict.pop() -- cgit v1.2.3 From ed21703046eaef34f5dca064f991ad1858026cf8 Mon Sep 17 00:00:00 2001 From: Danijel Anđelković Date: Thu, 5 May 2022 00:29:48 +0200 Subject: Izbrisao console log. --- backend/microservice/api/newmlservice.py | 21 +++++++-------------- .../src/app/_elements/folder/folder.component.ts | 5 +---- frontend/src/app/_elements/graph/graph.component.ts | 2 +- .../_elements/metric-view/metric-view.component.ts | 2 +- .../notifications/notifications.component.ts | 4 ++-- .../app/_elements/playlist/playlist.component.ts | 2 +- 6 files changed, 13 insertions(+), 23 deletions(-) (limited to 'backend/microservice/api') diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index 826ac7cb..85d8fb71 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -130,7 +130,7 @@ def returnColumnsInfo(dataset): #print(NullRows) #print(len(NullRows)) allNullRows=len(NullRows) - print(cMatrix.to_json(orient='index')) + #print(cMatrix.to_json(orient='index')) #json.loads()['data'] return {'columnInfo':dict,'allNullColl':int(allNullCols),'allNullRows':int(allNullRows),'rowCount':int(rowCount),'colCount':int(colCount),'cMatrix':json.loads(cMatrix.to_json(orient='split'))['data']} @@ -185,7 +185,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): col=columnInfo[i] if(columnTypes[i]=="categorical"): data[col['columnName']]=data[col['columnName']].apply(str) - kategorijskekolone.append(col['coumnName']) + kategorijskekolone.append(col['columnName']) #kategorijskekolone=data.select_dtypes(include=['object']).columns print(kategorijskekolone) ###NULL @@ -367,7 +367,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt, metrics =paramsModel['metrics']) - history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=float(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) hist=history.history #plt.plot(hist['accuracy']) @@ -421,14 +421,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics =paramsModel['metrics']) - print('AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA') - print(x_train) - print('AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA') - print(y_train) - print('AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA') - - - history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=float(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) hist=history.history y_pred=classifier.predict(x_test) y_pred=(y_pred>=0.5).astype('int') @@ -473,11 +466,11 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.add(tf.keras.layers.Dense(units=paramsModel['layers'][i+1]['neurons'], activation=paramsModel['layers'][i+1]['activationFunction'],kernel_regularizer=kernelreg, bias_regularizer=biasreg, activity_regularizer=activityreg))#i-ti skriveni sloj - classifier.add(tf.keras.layers.Dense(units=1),activation=paramsModel['outputLayerActivationFunction']) + classifier.add(tf.keras.layers.Dense(units=1,activation=paramsModel['outputLayerActivationFunction'])) classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics =paramsModel['metrics']) - history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=float(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) hist=history.history y_pred=classifier.predict(x_test) #print(classifier.evaluate(x_test, y_test)) @@ -647,7 +640,7 @@ def manageH5(dataset,params,h5model): h5model.compile(loss=params['lossFunction'], optimizer=params['optimizer'], metrics=params['metrics']) - history=h5model.fit(x2, y2, epochs = params['epochs'],batch_size=params['batchSize']) + history=h5model.fit(x2, y2, epochs = params['epochs'],batch_size=int(params['batchSize'])) y_pred2=h5model.predict(x2) diff --git a/frontend/src/app/_elements/folder/folder.component.ts b/frontend/src/app/_elements/folder/folder.component.ts index d5a7a85c..6ca0faa8 100644 --- a/frontend/src/app/_elements/folder/folder.component.ts +++ b/frontend/src/app/_elements/folder/folder.component.ts @@ -233,15 +233,12 @@ export class FolderComponent implements AfterViewInit { deleteFile(file: FolderFile, event: Event) { event.stopPropagation(); - console.log('delete'); + //console.log('delete'); switch (this.type) { case FolderType.Dataset: this.datasetsService.deleteDataset(file).subscribe((response) => { - console.log(this.files, this.filteredFiles) this.filteredFiles.splice(this.filteredFiles.indexOf(file), 1); - console.log(this.files, this.filteredFiles) this.refreshFiles(null); - console.log(this.files, this.filteredFiles) }); break; case FolderType.Model: diff --git a/frontend/src/app/_elements/graph/graph.component.ts b/frontend/src/app/_elements/graph/graph.component.ts index 73c3b1ab..da2c7767 100644 --- a/frontend/src/app/_elements/graph/graph.component.ts +++ b/frontend/src/app/_elements/graph/graph.component.ts @@ -43,7 +43,7 @@ export class GraphComponent implements AfterViewInit { window.addEventListener('resize', () => { this.resize() }); this.update(); this.resize(); - console.log(this.layers); + //console.log(this.layers); } layers: Node[][] = []; diff --git a/frontend/src/app/_elements/metric-view/metric-view.component.ts b/frontend/src/app/_elements/metric-view/metric-view.component.ts index 3840692a..6fd2f320 100644 --- a/frontend/src/app/_elements/metric-view/metric-view.component.ts +++ b/frontend/src/app/_elements/metric-view/metric-view.component.ts @@ -28,7 +28,7 @@ export class MetricViewComponent implements OnInit { myEpochs.push(epoch + 1); for (let key in metrics) { let value = metrics[key]; - console.log(key, ':::', value, epoch); + //console.log(key, ':::', value, epoch); if (key === 'accuracy') { myAcc.push(parseFloat(value)); } diff --git a/frontend/src/app/_elements/notifications/notifications.component.ts b/frontend/src/app/_elements/notifications/notifications.component.ts index d64530b9..5716c1e6 100644 --- a/frontend/src/app/_elements/notifications/notifications.component.ts +++ b/frontend/src/app/_elements/notifications/notifications.component.ts @@ -24,8 +24,8 @@ export class NotificationsComponent implements OnInit { this.signalRService.hubConnection.on("NotifyEpoch", (mName: string, mId: string, stat: string, totalEpochs: number, currentEpoch: number) => { const existingNotification = this.notifications.find(x => x.id === mId) const progress = ((currentEpoch + 1) / totalEpochs); - console.log("Ukupno epoha", totalEpochs, "Trenutna epoha:", currentEpoch); - console.log("stat:", stat); + //console.log("Ukupno epoha", totalEpochs, "Trenutna epoha:", currentEpoch); + //console.log("stat:", stat); if (!existingNotification) this.notifications.push(new Notification(`Treniranje modela: ${mName}`, mId, progress, true)); else { diff --git a/frontend/src/app/_elements/playlist/playlist.component.ts b/frontend/src/app/_elements/playlist/playlist.component.ts index 7529b36b..7f476178 100644 --- a/frontend/src/app/_elements/playlist/playlist.component.ts +++ b/frontend/src/app/_elements/playlist/playlist.component.ts @@ -44,6 +44,6 @@ export class PlaylistComponent implements OnInit { } }); - console.log(this.tableDatas); + //console.log(this.tableDatas); } } -- cgit v1.2.3 From 90dfdda35ce378808b3567b0addee603112ef756 Mon Sep 17 00:00:00 2001 From: Danijel Anđelković Date: Thu, 5 May 2022 00:56:30 +0200 Subject: Ispravio BUG u linechartu gde se vise puta iscrtavao isti model. --- backend/microservice/api/newmlservice.py | 10 ++--- .../_charts/line-chart/line-chart.component.ts | 48 +++++++++++----------- .../app/_pages/experiment/experiment.component.ts | 3 ++ 3 files changed, 32 insertions(+), 29 deletions(-) (limited to 'backend/microservice/api') diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index 85d8fb71..2f08d4b4 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -183,7 +183,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): columnTypes=paramsExperiment['columnTypes'] for i in range(len(columnInfo)): col=columnInfo[i] - if(columnTypes[i]=="categorical"): + if(columnTypes[i]=="categorical" and col['columnName'] in paramsExperiment['inputColumns']): data[col['columnName']]=data[col['columnName']].apply(str) kategorijskekolone.append(col['columnName']) #kategorijskekolone=data.select_dtypes(include=['object']).columns @@ -365,7 +365,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): - classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt, metrics =paramsModel['metrics']) + classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt, metrics = ['accuracy','mae','mse']) history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) @@ -419,7 +419,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.add(tf.keras.layers.Dense(units=1, activation=paramsModel['outputLayerActivationFunction']))#izlazni sloj - classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics =paramsModel['metrics']) + classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics = ['accuracy','mae','mse']) history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) hist=history.history @@ -468,7 +468,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.add(tf.keras.layers.Dense(units=1,activation=paramsModel['outputLayerActivationFunction'])) - classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics =paramsModel['metrics']) + classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics = ['accuracy','mae','mse']) history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id'])) hist=history.history @@ -638,7 +638,7 @@ def manageH5(dataset,params,h5model): h5model.summary() #ann_viz(h5model, title="My neural network") - h5model.compile(loss=params['lossFunction'], optimizer=params['optimizer'], metrics=params['metrics']) + h5model.compile(loss=params['lossFunction'], optimizer=params['optimizer'], metrics = ['accuracy','mae','mse']) history=h5model.fit(x2, y2, epochs = params['epochs'],batch_size=int(params['batchSize'])) diff --git a/frontend/src/app/_elements/_charts/line-chart/line-chart.component.ts b/frontend/src/app/_elements/_charts/line-chart/line-chart.component.ts index 34df38bc..655db9ec 100644 --- a/frontend/src/app/_elements/_charts/line-chart/line-chart.component.ts +++ b/frontend/src/app/_elements/_charts/line-chart/line-chart.component.ts @@ -9,12 +9,12 @@ import { Chart } from 'chart.js'; export class LineChartComponent implements AfterViewInit { - dataAcc: number[] = [2,3,5,5,6,7,8,8,4,6,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]; - dataMAE: number[] = [2,3,5,5,6,7,8,8,4,6,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]; - dataMSE: number[] = [2,3,5,5,6,7,8,8,4,6,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]; - dataLOSS: number[] =[2,3,5,5,6,7,8,8,4,6,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]; + dataAcc: number[] = []; + dataMAE: number[] = []; + dataMSE: number[] = []; + dataLOSS: number[] = []; - dataEpoch: number[] = [2,3,5,5,6,7,8,8,4,6,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97,2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]; + dataEpoch: number[] = []; constructor() { /*let i = 0; @@ -77,28 +77,28 @@ export class LineChartComponent implements AfterViewInit { }, options: { scales: { - x:{ - ticks: { - color: 'white' - }, - grid: { - color: "rgba(0, 99, 171, 0.5)" - } + x: { + ticks: { + color: 'white' }, - y: { - beginAtZero: true, - ticks: { - color: 'white' - }, - grid: { - color: "rgba(0, 99, 171, 0.5)" - } + grid: { + color: "rgba(0, 99, 171, 0.5)" } - + }, + y: { + beginAtZero: true, + ticks: { + color: 'white' + }, + grid: { + color: "rgba(0, 99, 171, 0.5)" + } + } + } - - - } + + + } } ); } diff --git a/frontend/src/app/_pages/experiment/experiment.component.ts b/frontend/src/app/_pages/experiment/experiment.component.ts index c4d6063c..1dc18a78 100644 --- a/frontend/src/app/_pages/experiment/experiment.component.ts +++ b/frontend/src/app/_pages/experiment/experiment.component.ts @@ -75,6 +75,9 @@ export class ExperimentComponent implements AfterViewInit { if (this.signalRService.hubConnection) { this.signalRService.hubConnection.on("NotifyEpoch", (mName: string, mId: string, stat: string, totalEpochs: number, currentEpoch: number) => { console.log(this.modelToTrain?._id, mId); + if (currentEpoch == 0) { + this.history = []; + } if (this.modelToTrain?._id == mId) { stat = stat.replace(/'/g, '"'); //console.log('JSON', this.trainingResult); -- cgit v1.2.3