From 73a539f449f2f6ec7bc7adaa18ebbe1b1b45ad9c Mon Sep 17 00:00:00 2001 From: TAMARA JERINIC Date: Sat, 16 Apr 2022 00:42:36 +0200 Subject: Omogućeno prikupljanje rezultata metrika nakon završenog treniranja modela. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- backend/microservice/api/newmlservice.py | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index d19a4e44..ecadb0f4 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -21,6 +21,7 @@ from sklearn.model_selection import train_test_split from dataclasses import dataclass import statistics as s from sklearn.metrics import roc_auc_score + #from ann_visualizer.visualize import ann_viz; def returnColumnsInfo(dataset): dict=[] @@ -224,7 +225,7 @@ def train(dataset, params, callback): # # ###OPTIMIZATORI - + """ if(params['optimizer']=='adam'): opt=tf.keras.optimizers.Adam(learning_rate=params['learningRate']) @@ -276,7 +277,7 @@ def train(dataset, params, callback): activityreg=tf.keras.regularizers.l2(reg['activityRate']) elif(reg['kernelType']=='l1l2'): activityreg=tf.keras.regularizers.l1_l2(l1=reg['activityRate'][0],l2=reg['activityRate'][1]) - + """ if(problem_type=='multi-klasifikacioni'): #print('multi') @@ -293,17 +294,19 @@ def train(dataset, params, callback): classifier.compile(loss =params["lossFunction"] , optimizer = params['optimizer'] , metrics =params['metrics']) history=classifier.fit(x_train, y_train, epochs = params['epochs'],batch_size=params['batchSize']) - + + hist=history.history + y_pred=classifier.predict(x_test) y_pred=np.argmax(y_pred,axis=1) - #print(y_pred.flatten()) - #print(y_test) + scores = classifier.evaluate(x_test, y_test) #print("\n%s: %.2f%%" % (classifier.metrics_names[1], scores[1]*100)) classifier.save("temp/"+params['name'], save_format='h5') #vizuelizacija u python-u #from ann_visualizer.visualize import ann_viz; #ann_viz(classifier, title="My neural network") + return hist elif(problem_type=='binarni-klasifikacioni'): #print('*************************************************************************binarni') @@ -318,7 +321,7 @@ def train(dataset, params, callback): classifier.compile(loss =params["lossFunction"] , optimizer = params['optimizer'] , metrics =params['metrics']) history=classifier.fit(x_train, y_train, epochs = params['epochs'],batch_size=params['batchSize']) - + hist=history.history y_pred=classifier.predict(x_test) y_pred=(y_pred>=0.5).astype('int') @@ -330,6 +333,7 @@ def train(dataset, params, callback): #ann_viz(classifier, title="My neural network") classifier.save("temp/"+params['name'], save_format='h5') + return hist elif(problem_type=='regresioni'): classifier=tf.keras.Sequential() @@ -343,9 +347,10 @@ def train(dataset, params, callback): classifier.compile(loss =params["lossFunction"] , optimizer = params['optimizer'] , metrics =params['metrics']) history=classifier.fit(x_train, y_train, epochs = params['epochs'],batch_size=params['batchSize']) + hist=history.history y_pred=classifier.predict(x_test) #print(classifier.evaluate(x_test, y_test)) - + return hist def roc_auc_score_multiclass(actual_class, pred_class, average = "macro"): #creating a set of all the unique classes using the actual class list -- cgit v1.2.3 From e8db6c2081155f9c4fed7c8a06e37e89a7398101 Mon Sep 17 00:00:00 2001 From: Ivan Ljubisavljevic Date: Sat, 16 Apr 2022 14:16:04 +0200 Subject: Zavrsen predict i povezan sa ml-om. #105 --- backend/api/api/Controllers/PredictorController.cs | 19 ++++++++++++++----- backend/api/api/Models/Predictor.cs | 1 + backend/api/api/Services/IMlConnectionService.cs | 3 +++ backend/api/api/Services/MlConnectionService.cs | 18 ++++++++++++++++-- 4 files changed, 34 insertions(+), 7 deletions(-) diff --git a/backend/api/api/Controllers/PredictorController.cs b/backend/api/api/Controllers/PredictorController.cs index 233ea401..87c32048 100644 --- a/backend/api/api/Controllers/PredictorController.cs +++ b/backend/api/api/Controllers/PredictorController.cs @@ -15,12 +15,14 @@ namespace api.Controllers private readonly IPredictorService _predictorService; private IJwtToken jwtToken; private readonly IMlConnectionService _mlConnectionService; + private readonly IExperimentService _experimentService; - public PredictorController(IPredictorService predictorService, IConfiguration configuration, IJwtToken Token, IMlConnectionService mlConnectionService) + public PredictorController(IPredictorService predictorService, IConfiguration configuration, IJwtToken Token, IMlConnectionService mlConnectionService, IExperimentService experimentService) { _predictorService = predictorService; jwtToken = Token; _mlConnectionService = mlConnectionService; + _experimentService = experimentService; } public string getUsername() @@ -160,7 +162,7 @@ namespace api.Controllers // POST api//usepredictor {predictor,inputs} [HttpPost("usepredictor/{id}")] [Authorize(Roles = "User,Guest")] - public ActionResult UsePredictor(String id, [FromBody] PredictorColumns[] inputs) + public async Task UsePredictor(String id, [FromBody] PredictorColumns[] inputs) { string username = getUsername(); @@ -168,10 +170,17 @@ namespace api.Controllers return BadRequest(); Predictor predictor = _predictorService.GetPredictor(username, id); - + + Experiment e = _experimentService.Get(predictor.experimentId); + + string result = await _mlConnectionService.Predict(predictor, e, inputs); + + //salji ml + + /* foreach(PredictorColumns i in inputs) - Debug.WriteLine(i.value.ToString()); - return NoContent(); + Debug.WriteLine(i.value.ToString());*/ + return Ok(result); } // PUT api//{name} diff --git a/backend/api/api/Models/Predictor.cs b/backend/api/api/Models/Predictor.cs index b1d6444b..3f9889be 100644 --- a/backend/api/api/Models/Predictor.cs +++ b/backend/api/api/Models/Predictor.cs @@ -18,6 +18,7 @@ namespace api.Models public bool accessibleByLink { get; set; } public DateTime dateCreated { get; set; } public string experimentId { get; set; } + public string h5FileId { get; set; } } } diff --git a/backend/api/api/Services/IMlConnectionService.cs b/backend/api/api/Services/IMlConnectionService.cs index d161bf49..d5dda9f2 100644 --- a/backend/api/api/Services/IMlConnectionService.cs +++ b/backend/api/api/Services/IMlConnectionService.cs @@ -8,6 +8,9 @@ namespace api.Services Task SendModelAsync(object model, object dataset); Task PreProcess(Dataset dataset, string filePath,string id); Task TrainModel(Model model, Experiment experiment, string filePath, Dataset dataset, string id); + + Task Predict(Predictor predictor, Experiment experiment, PredictorColumns[] inputs); + //Task PreProcess(Dataset dataset, byte[] file, string filename); } } \ No newline at end of file diff --git a/backend/api/api/Services/MlConnectionService.cs b/backend/api/api/Services/MlConnectionService.cs index bde9ce4c..4363b4ad 100644 --- a/backend/api/api/Services/MlConnectionService.cs +++ b/backend/api/api/Services/MlConnectionService.cs @@ -14,8 +14,9 @@ namespace api.Services private readonly IModelService _modelService; private readonly IHubContext _ichat; private readonly IConfiguration _configuration; + private readonly IFileService _fileService; - public MlConnectionService(IConfiguration configuration,IDatasetService datasetService,IHubContext ichat) + public MlConnectionService(IConfiguration configuration,IDatasetService datasetService,IHubContext ichat, IFileService fileService) { _configuration = configuration; @@ -23,6 +24,7 @@ namespace api.Services _datasetService=datasetService; _ichat=ichat; + _fileService = fileService; } public async Task SendModelAsync(object model, object dataset)//Don't Use @@ -67,8 +69,20 @@ namespace api.Services } - + public async Task Predict(Predictor predictor, Experiment experiment, PredictorColumns[] inputs) + { + string filePath = _fileService.GetFilePath(predictor.h5FileId, predictor.username); + + var request = new RestRequest("predict", Method.Post); + request.AddParameter("predictor", JsonConvert.SerializeObject(predictor)); + request.AddParameter("experiment", JsonConvert.SerializeObject(experiment)); + request.AddFile("file", filePath); + request.AddHeader("Content-Type", "multipart/form-data"); + + var result = await this.client.ExecuteAsync(request); + return result.Content; + } } } -- cgit v1.2.3 From d76cb349ef8d5254780e3ffb6afa7080513f2332 Mon Sep 17 00:00:00 2001 From: Danijel Anđelković Date: Sat, 16 Apr 2022 18:17:07 +0200 Subject: Update-ovao ML kontroler za predict. --- backend/microservice/api/config.py | 2 +- backend/microservice/api/controller.py | 16 ++++++++-------- backend/microservice/api/newmlservice.py | 5 +++++ 3 files changed, 14 insertions(+), 9 deletions(-) diff --git a/backend/microservice/api/config.py b/backend/microservice/api/config.py index 2b6fbe89..8fb088a7 100644 --- a/backend/microservice/api/config.py +++ b/backend/microservice/api/config.py @@ -1,2 +1,2 @@ api_url = "http://localhost:5283/api" - +hostIP = "127.0.0.1:5543" \ No newline at end of file diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py index 8e12c41d..d7564b70 100644 --- a/backend/microservice/api/controller.py +++ b/backend/microservice/api/controller.py @@ -9,7 +9,7 @@ import config app = flask.Flask(__name__) app.config["DEBUG"] = True -app.config["SERVER_NAME"] = "127.0.0.1:5543" +app.config["SERVER_NAME"] = config.hostIP class train_callback(tf.keras.callbacks.Callback): def __init__(self, x_test, y_test): @@ -33,19 +33,19 @@ def train(): paramsExperiment = json.loads(request.form["experiment"]) paramsDataset = json.loads(request.form["dataset"]) #dataset, paramsModel, paramsExperiment, callback) - result = newmlservice.train(data, paramsModel, paramsExperiment,paramsDataset, train_callback) + result = newmlservice.train(data, paramsModel, paramsExperiment, paramsDataset, train_callback) print(result) return jsonify(result) @app.route('/predict', methods = ['POST']) def predict(): - f = request.json['filepath'] - dataset = pd.read_csv(f) - m = request.json['modelpath'] - model = tf.keras.models.load_model(m) + h5 = request.files.get("h5file") + model = tf.keras.models.load_model(h5) + paramsExperiment = json.loads(request.form["experiment"]) + paramsPredictor = json.loads(request.form["predictor"]) print("********************************model loaded*******************************") - newmlservice.manageH5(dataset,request.json['model'],model) - return "done" + result = newmlservice.predict(paramsExperiment, paramsPredictor, model) + return result @app.route('/preprocess',methods=['POST']) def returnColumnsInfo(): diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index ecadb0f4..74ad232e 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -432,6 +432,11 @@ def train(dataset, params, callback): micro_averaged_f1=metrics.f1_score(y_test, y_pred, average = 'micro') roc_auc_dict=roc_auc_score_multiclass(y_test, y_pred) ''' +def predict(experiment, predictor, model) { + #model.predict() + # ovo je pre bilo manageH5 + return "TODO" +} def manageH5(dataset,params,h5model): problem_type = params["type"] -- cgit v1.2.3 From 717e15a9e0d35148a3cb0015b4b11b3abd291390 Mon Sep 17 00:00:00 2001 From: Ognjen Cirkovic Date: Sat, 16 Apr 2022 18:36:22 +0200 Subject: Updajtovan Cors. Sve se uzima iz konfiguracionog fajla --- backend/api/api/Program.cs | 5 +-- backend/api/api/Properties/launchSettings.json | 46 +++++++++++--------------- backend/api/api/appsettings.json | 41 ++++++++++++----------- 3 files changed, 43 insertions(+), 49 deletions(-) diff --git a/backend/api/api/Program.cs b/backend/api/api/Program.cs index 576093fe..71509b38 100644 --- a/backend/api/api/Program.cs +++ b/backend/api/api/Program.cs @@ -64,11 +64,12 @@ builder.Services.Configure(x => builder.Services.AddSignalR(); builder.Services.AddControllers(); - +string frontApi = builder.Configuration.GetValue("AppSettings:FrontApi"); +string mlApi = builder.Configuration.GetValue("AppSettings:MlApi"); builder.Services.AddCors(options => { options.AddPolicy("CorsPolicy", builder => builder - .WithOrigins("http://localhost:4200") + .WithOrigins(frontApi, mlApi) .AllowAnyMethod() .AllowAnyHeader() .AllowCredentials()); diff --git a/backend/api/api/Properties/launchSettings.json b/backend/api/api/Properties/launchSettings.json index 5c9dd2a8..f6c3fe8b 100644 --- a/backend/api/api/Properties/launchSettings.json +++ b/backend/api/api/Properties/launchSettings.json @@ -1,31 +1,23 @@ { - "$schema": "https://json.schemastore.org/launchsettings.json", - "iisSettings": { - "windowsAuthentication": false, - "anonymousAuthentication": true, - "iisExpress": { - "applicationUrl": "http://localhost:61918", - "sslPort": 0 - } - }, - "profiles": { - "api": { - "commandName": "Project", - "dotnetRunMessages": true, - "launchBrowser": false, - "launchUrl": "", - "applicationUrl": "http://localhost:5283", - "environmentVariables": { - "ASPNETCORE_ENVIRONMENT": "Development" - } + "$schema": "https://json.schemastore.org/launchsettings.json", + "iisSettings": { + "windowsAuthentication": false, + "anonymousAuthentication": true, + "iisExpress": { + "applicationUrl": "http://localhost:61918", + "sslPort": 0 + } }, - "IIS Express": { - "commandName": "IISExpress", - "launchBrowser": false, - "launchUrl": "", - "environmentVariables": { - "ASPNETCORE_ENVIRONMENT": "Development" - } + "profiles": { + "api": { + "commandName": "Project", + "dotnetRunMessages": true, + "launchBrowser": false, + "launchUrl": "", + "applicationUrl": "http://localhost:5283", + "environmentVariables": { + "ASPNETCORE_ENVIRONMENT": "Development" + } + } } - } } diff --git a/backend/api/api/appsettings.json b/backend/api/api/appsettings.json index 42f62b75..e96549a8 100644 --- a/backend/api/api/appsettings.json +++ b/backend/api/api/appsettings.json @@ -1,27 +1,28 @@ { "AppSettings": { "JwtToken": "2mnttqPtRb4GIWHFtagm", - "MlApi": "http://127.0.0.1:5543" + "MlApi": "http://127.0.0.1:5543", + "FrontApi": "http://localhost:4200" }, - "Logging": { - "LogLevel": { - "Default": "Information", - "Microsoft.AspNetCore": "Warning" - } - }, - "AllowedHosts": "*", - "UserStoreDatabaseSettings": { - /* LocalHost*/ + "Logging": { + "LogLevel": { + "Default": "Information", + "Microsoft.AspNetCore": "Warning" + } + }, + "AllowedHosts": "*", + "UserStoreDatabaseSettings": { + /* LocalHost*/ - "ConnectionString": "mongodb://127.0.0.1:27017/", - "DatabaseName": "si_project", - "CollectionName": "users", - "DatasetCollectionName": "Dataset", - "ModelCollectionName": "Model", - "PredictorCollectionName": "Predictor", - "FilesCollectionName": "Files", - "ExperimentCollectionName": "Experiment" - /* + "ConnectionString": "mongodb://127.0.0.1:27017/", + "DatabaseName": "si_project", + "CollectionName": "users", + "DatasetCollectionName": "Dataset", + "ModelCollectionName": "Model", + "PredictorCollectionName": "Predictor", + "FilesCollectionName": "Files", + "ExperimentCollectionName": "Experiment" + /* "ConnectionString": "mongodb+srv://si_user:si_user@sidatabase.twtfm.mongodb.net/myFirstDatabase?retryWrites=true&w=majority", "DatabaseName": "si_db", "CollectionName": "users", @@ -30,5 +31,5 @@ "PredictorCollectionName": "Predictor", "FilesCollectionName": "Files", "ExperimentCollectionName": "Experiment" */ - } + } } \ No newline at end of file -- cgit v1.2.3 From 4a6665959aa8b17e3dd0235530b46c3315d520db Mon Sep 17 00:00:00 2001 From: Ognjen Cirkovic Date: Sat, 16 Apr 2022 18:41:19 +0200 Subject: Fix. --- backend/microservice/api/newmlservice.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index 74ad232e..3427e287 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -432,11 +432,11 @@ def train(dataset, params, callback): micro_averaged_f1=metrics.f1_score(y_test, y_pred, average = 'micro') roc_auc_dict=roc_auc_score_multiclass(y_test, y_pred) ''' -def predict(experiment, predictor, model) { +def predict(experiment, predictor, model): #model.predict() # ovo je pre bilo manageH5 return "TODO" -} + def manageH5(dataset,params,h5model): problem_type = params["type"] -- cgit v1.2.3 From 74e467d41e7234bc806e9ba30c6766791601ec6b Mon Sep 17 00:00:00 2001 From: Ognjen Cirkovic Date: Sat, 16 Apr 2022 19:13:02 +0200 Subject: Izmenjeni predictor i predictor servis. Poruka se salje korisniku po zavrsetku treniranja sa id prediktora. --- backend/api/api/Controllers/PredictorController.cs | 76 ++++++++++++---------- backend/api/api/Models/Predictor.cs | 13 +++- backend/api/api/Services/IPredictorService.cs | 23 +++---- backend/api/api/Services/MlConnectionService.cs | 6 +- backend/api/api/Services/PredictorService.cs | 16 ++--- 5 files changed, 69 insertions(+), 65 deletions(-) diff --git a/backend/api/api/Controllers/PredictorController.cs b/backend/api/api/Controllers/PredictorController.cs index 87c32048..481334e9 100644 --- a/backend/api/api/Controllers/PredictorController.cs +++ b/backend/api/api/Controllers/PredictorController.cs @@ -5,6 +5,7 @@ using Microsoft.AspNetCore.Mvc; using Microsoft.Net.Http.Headers; using System.Net.Http.Headers; using System.Diagnostics; +using Microsoft.AspNetCore.SignalR; namespace api.Controllers { @@ -16,13 +17,19 @@ namespace api.Controllers private IJwtToken jwtToken; private readonly IMlConnectionService _mlConnectionService; private readonly IExperimentService _experimentService; + private readonly IUserService _userService; + private readonly IHubContext _ichat; + private readonly IModelService _modelService; - public PredictorController(IPredictorService predictorService, IConfiguration configuration, IJwtToken Token, IMlConnectionService mlConnectionService, IExperimentService experimentService) + public PredictorController(IPredictorService predictorService, IConfiguration configuration, IJwtToken Token, IMlConnectionService mlConnectionService, IExperimentService experimentService,IUserService userService, IHubContext ichat,IModelService modelService) { _predictorService = predictorService; jwtToken = Token; _mlConnectionService = mlConnectionService; _experimentService = experimentService; + _userService = userService; + _ichat = ichat; + _modelService = modelService; } public string getUsername() @@ -65,17 +72,18 @@ namespace api.Controllers //SEARCH za predictore (public ili private sa ovim imenom ) // GET api//search/{name} - [HttpGet("search/{name}")] - [Authorize(Roles = "User")] - public ActionResult> Search(string name) - { - string username = getUsername(); + + //[HttpGet("search/{name}")] + //[Authorize(Roles = "User")] + //public ActionResult> Search(string name) + //{ + // string username = getUsername(); - if (username == null) - return BadRequest(); + // if (username == null) + // return BadRequest(); - return _predictorService.SearchPredictors(name, username); - } + // return _predictorService.SearchPredictors(name, username); + //} // GET api//getpredictor/{name} [HttpGet("getpredictor/{id}")] @@ -98,17 +106,17 @@ namespace api.Controllers // GET api//{name} [HttpGet("{name}")] [Authorize(Roles = "User")] - public ActionResult Get(string name) + public ActionResult Get(string id) { string username = getUsername(); if (username == null) return BadRequest(); - var predictor = _predictorService.GetOnePredictor(username, name); + var predictor = _predictorService.GetOnePredictor(id); if (predictor == null) - return NotFound($"Predictor with name = {name} not found or predictor is not public"); + return NotFound($"Predictor with id = {id} not found or predictor is not public"); return predictor; } @@ -144,19 +152,17 @@ namespace api.Controllers // POST api//add [HttpPost("add")] - [Authorize(Roles = "User")] - public ActionResult Post([FromBody] Predictor predictor) + public async Task> Post([FromBody] Predictor predictor) { - var existingPredictor = _predictorService.GetOnePredictor(predictor.username, predictor.name); - - if (existingPredictor != null) - return NotFound($"Predictor with name = {predictor.name} exisits"); - else - { - _predictorService.Create(predictor); - - return CreatedAtAction(nameof(Get), new { id = predictor._id }, predictor); - } + var user=_userService.GetUserByUsername(predictor.username); + var model = _modelService.GetOneModel(predictor.modelId); + if (model == null || user==null) + return BadRequest("Model not found or user doesnt exist"); + _predictorService.Create(predictor); + if (ChatHub.CheckUser(user._id)) + await _ichat.Clients.Client(ChatHub.Users[user._id]).SendAsync("NotifyPredictor", predictor._id,model.name); + return CreatedAtAction(nameof(Get), new { id = predictor._id }, predictor); + } // POST api//usepredictor {predictor,inputs} @@ -186,42 +192,42 @@ namespace api.Controllers // PUT api//{name} [HttpPut("{name}")] [Authorize(Roles = "User")] - public ActionResult Put(string name, [FromBody] Predictor predictor) + public ActionResult Put(string id, [FromBody] Predictor predictor) { string username = getUsername(); if (username == null) return BadRequest(); - var existingPredictor = _predictorService.GetOnePredictor(username, name); + var existingPredictor = _predictorService.GetOnePredictor(id); //ne mora da se proverava if (existingPredictor == null) - return NotFound($"Predictor with name = {name} or user with username = {username} not found"); + return NotFound($"Predictor with id = {id} or user with username = {username} not found"); - _predictorService.Update(username, name, predictor); + _predictorService.Update(id, predictor); - return Ok($"Predictor with name = {name} updated"); + return Ok($"Predictor with id = {id} updated"); } // DELETE api//name [HttpDelete("{name}")] [Authorize(Roles = "User")] - public ActionResult Delete(string name) + public ActionResult Delete(string id) { string username = getUsername(); if (username == null) return BadRequest(); - var predictor = _predictorService.GetOnePredictor(username, name); + var predictor = _predictorService.GetOnePredictor(id); if (predictor == null) - return NotFound($"Predictor with name = {name} or user with username = {username} not found"); + return NotFound($"Predictor with id = {id} or user with username = {username} not found"); - _predictorService.Delete(predictor.username, predictor.name); + _predictorService.Delete(id); - return Ok($"Predictor with name = {name} deleted"); + return Ok($"Predictor with id = {id} deleted"); } } diff --git a/backend/api/api/Models/Predictor.cs b/backend/api/api/Models/Predictor.cs index 3f9889be..26371d2a 100644 --- a/backend/api/api/Models/Predictor.cs +++ b/backend/api/api/Models/Predictor.cs @@ -10,17 +10,26 @@ namespace api.Models [BsonRepresentation(BsonType.ObjectId)]//mongo data type to .net public string _id { get; set; } public string username { get; set; } - public string name { get; set; } - public string description { get; set; } + //public string name { get; set; } + //public string description { get; set; } public string[] inputs { get; set; } public string output { get; set; } public bool isPublic { get; set; } public bool accessibleByLink { get; set; } public DateTime dateCreated { get; set; } public string experimentId { get; set; } + public string modelId { get; set; } public string h5FileId { get; set; } + public Metric[] metrics { get; set; } + } + public class Metric + { + string Name { get; set; } + string JsonValue { get; set; } + + } } /* diff --git a/backend/api/api/Services/IPredictorService.cs b/backend/api/api/Services/IPredictorService.cs index 729dd0b6..7c31215e 100644 --- a/backend/api/api/Services/IPredictorService.cs +++ b/backend/api/api/Services/IPredictorService.cs @@ -1,19 +1,16 @@ -using System; -using api.Models; +using api.Models; namespace api.Services { - public interface IPredictorService - { - Predictor GetOnePredictor(string username, string name); - Predictor GetPredictor(string username, string GetPredictor); - List SearchPredictors(string name, string username); + public interface IPredictorService + { + Predictor Create(Predictor predictor); + void Delete(string id); List GetMyPredictors(string username); - List SortPredictors(string username, bool ascdsc, int latest); + Predictor GetOnePredictor(string id); + Predictor GetPredictor(string username, string id); List GetPublicPredictors(); - Predictor Create(Predictor predictor); - void Update(string username, string name, Predictor predictor); - void Delete(string username, string name); + List SortPredictors(string username, bool ascdsc, int latest); + void Update(string id, Predictor predictor); } -} - +} \ No newline at end of file diff --git a/backend/api/api/Services/MlConnectionService.cs b/backend/api/api/Services/MlConnectionService.cs index 4363b4ad..22db0aea 100644 --- a/backend/api/api/Services/MlConnectionService.cs +++ b/backend/api/api/Services/MlConnectionService.cs @@ -43,11 +43,7 @@ namespace api.Services //request.AddFile("file", file,filename); request.AddFile("file", filePath); request.AddHeader("Content-Type", "multipart/form-data"); - var result = await this.client.ExecuteAsync(request); - - if (ChatHub.CheckUser(id)) - await _ichat.Clients.Client(ChatHub.Users[id]).SendAsync("NotifyModel",model.name,model._id); - + this.client.ExecuteAsync(request); return; } diff --git a/backend/api/api/Services/PredictorService.cs b/backend/api/api/Services/PredictorService.cs index b89eaded..144248d4 100644 --- a/backend/api/api/Services/PredictorService.cs +++ b/backend/api/api/Services/PredictorService.cs @@ -14,10 +14,6 @@ namespace api.Services _predictor = database.GetCollection(settings.PredictorCollectionName); } - public List SearchPredictors(string name, string username) - { - return _predictor.Find(predictor => predictor.name == name && predictor.isPublic == true).ToList(); - } public Predictor Create(Predictor predictor) { @@ -25,9 +21,9 @@ namespace api.Services return predictor; } - public void Delete(string username, string name) + public void Delete(string id) { - _predictor.DeleteOne(predictor => (predictor.username == username && predictor.name == name)); + _predictor.DeleteOne(predictor => (predictor._id == id)); } public List GetMyPredictors(string username) @@ -35,9 +31,9 @@ namespace api.Services return _predictor.Find(predictor => predictor.username == username).ToList(); } - public Predictor GetOnePredictor(string username, string name) + public Predictor GetOnePredictor(string id) { - return _predictor.Find(predictor => predictor.username == username && predictor.name == name).FirstOrDefault(); + return _predictor.Find(predictor => predictor._id == id).FirstOrDefault(); } public Predictor GetPredictor(string username, string id) @@ -62,9 +58,9 @@ namespace api.Services return _predictor.Find(predictor => predictor.isPublic == true).ToList(); } - public void Update(string username, string name, Predictor predictor) + public void Update(string id, Predictor predictor) { - _predictor.ReplaceOne(predictor => predictor.username == username && predictor.name == name, predictor); + _predictor.ReplaceOne(predictor => predictor._id == id, predictor); } } } -- cgit v1.2.3 From 0839b7a0217160214cce8ae881fa0b76810850df Mon Sep 17 00:00:00 2001 From: Ognjen Cirkovic Date: Sat, 16 Apr 2022 19:16:55 +0200 Subject: Uplodovanje h5 fajla vraca id tog fajla u bazi --- backend/api/api/Controllers/FileController.cs | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/backend/api/api/Controllers/FileController.cs b/backend/api/api/Controllers/FileController.cs index b9b31500..6888f1c7 100644 --- a/backend/api/api/Controllers/FileController.cs +++ b/backend/api/api/Controllers/FileController.cs @@ -105,7 +105,7 @@ namespace api.Controllers fileModel = _fileservice.Create(fileModel); - return Ok(fileModel); + return Ok(fileModel._id); } [HttpGet("csvread/{hasHeader}/{fileId}")] -- cgit v1.2.3 From fdd1bdcbe113c568dbeef4de6b9a5ad3c9652ef8 Mon Sep 17 00:00:00 2001 From: TAMARA JERINIC Date: Sat, 16 Apr 2022 19:42:35 +0200 Subject: Dodat zahtev za čuvanje h5 fajla treniranog modela. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- backend/microservice/api/controller.py | 14 +++++- backend/microservice/api/newmlservice.py | 77 +++++++++++++++++--------------- 2 files changed, 55 insertions(+), 36 deletions(-) diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py index d7564b70..d2b8ed2c 100644 --- a/backend/microservice/api/controller.py +++ b/backend/microservice/api/controller.py @@ -1,3 +1,4 @@ +from gc import callbacks import flask from flask import request, jsonify import newmlservice @@ -27,14 +28,25 @@ class train_callback(tf.keras.callbacks.Callback): @app.route('/train', methods = ['POST']) def train(): print("******************************TRAIN*************************************************") + f = request.files.get("file") data = pd.read_csv(f) paramsModel = json.loads(request.form["model"]) paramsExperiment = json.loads(request.form["experiment"]) paramsDataset = json.loads(request.form["dataset"]) #dataset, paramsModel, paramsExperiment, callback) - result = newmlservice.train(data, paramsModel, paramsExperiment, paramsDataset, train_callback) + filepath,result = newmlservice.train(data, paramsModel, paramsExperiment,paramsDataset, train_callback) + """ + f = request.json['filepath'] + dataset = pd.read_csv(f) + filepath,result=newmlservice.train(dataset,request.json['model'],train_callback) print(result) + """ + + url = config.api_url + "/file/h5" + files = {'file': open(filepath, 'rb')} + r=requests.post(url, files=files) + fileId=r.text return jsonify(result) @app.route('/predict', methods = ['POST']) diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index 3427e287..e81192ab 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -1,5 +1,6 @@ from enum import unique from itertools import count +import os import pandas as pd from sklearn import datasets, multiclass import tensorflow as tf @@ -21,7 +22,7 @@ from sklearn.model_selection import train_test_split from dataclasses import dataclass import statistics as s from sklearn.metrics import roc_auc_score - +import matplotlib.pyplot as plt #from ann_visualizer.visualize import ann_viz; def returnColumnsInfo(dataset): dict=[] @@ -113,25 +114,25 @@ class TrainingResult: metrics: dict ''' -def train(dataset, params, callback): - problem_type = params["type"] +def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): + problem_type = paramsModel["type"] #print(problem_type) data = pd.DataFrame() #print(data) - for col in params["inputColumns"]: + for col in paramsExperiment["inputColumns"]: #print(col) data[col]=dataset[col] - output_column = params["columnToPredict"] + output_column = paramsExperiment["columnToPredict"] data[output_column] = dataset[output_column] #print(data) ###NULL - null_value_options = params["nullValues"] - null_values_replacers = params["nullValuesReplacers"] + null_value_options = paramsExperiment["nullValues"] + null_values_replacers = paramsExperiment["nullValuesReplacers"] if(null_value_options=='replace'): #print("replace null") # - dict=params['null_values_replacers'] + dict=null_values_replacers while(len(dict)>0): replace=dict.pop() col=replace['column'] @@ -154,7 +155,7 @@ def train(dataset, params, callback): data.pop(col) # ### Enkodiranje - encoding=params["encoding"] + encoding=paramsExperiment["encoding"] if(encoding=='label'): encoder=LabelEncoder() for col in data.columns: @@ -211,8 +212,8 @@ def train(dataset, params, callback): # # Podela na test i trening skupove # - test=params["randomTestSetDistribution"] - randomOrder = params["randomOrder"] + test=paramsExperiment["randomTestSetDistribution"] + randomOrder = paramsExperiment["randomOrder"] if(randomOrder): random=123 else: @@ -278,49 +279,54 @@ def train(dataset, params, callback): elif(reg['kernelType']=='l1l2'): activityreg=tf.keras.regularizers.l1_l2(l1=reg['activityRate'][0],l2=reg['activityRate'][1]) """ - + filepath=os.path.join("temp/",paramsExperiment['_id']+"_"+paramsModel['_id']) if(problem_type=='multi-klasifikacioni'): #print('multi') classifier=tf.keras.Sequential() - classifier.add(tf.keras.layers.Dense(units=params['hiddenLayerNeurons'], activation=params['hiddenLayerActivationFunctions'][0],input_dim=x_train.shape[1]))#prvi skriveni + definisanje prethodnog-ulaznog - for i in range(params['hiddenLayers']-1):#ako postoji vise od jednog skrivenog sloja + classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][0],input_dim=x_train.shape[1]))#prvi skriveni + definisanje prethodnog-ulaznog + for i in range(paramsModel['hiddenLayers']-1):#ako postoji vise od jednog skrivenog sloja #print(i) - classifier.add(tf.keras.layers.Dense(units=params['hiddenLayerNeurons'], activation=params['hiddenLayerActivationFunctions'][i+1]))#i-ti skriveni sloj - classifier.add(tf.keras.layers.Dense(units=5, activation=params['outputLayerActivationFunction']))#izlazni sloj + classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][i+1]))#i-ti skriveni sloj + classifier.add(tf.keras.layers.Dense(units=5, activation=paramsModel['outputLayerActivationFunction']))#izlazni sloj - classifier.compile(loss =params["lossFunction"] , optimizer = params['optimizer'] , metrics =params['metrics']) + classifier.compile(loss =paramsModel["lossFunction"] , optimizer = paramsModel['optimizer'] , metrics =paramsModel['metrics']) - history=classifier.fit(x_train, y_train, epochs = params['epochs'],batch_size=params['batchSize']) + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=paramsModel['batchSize']) hist=history.history - + plt.plot(hist['accuracy']) + plt.show() y_pred=classifier.predict(x_test) y_pred=np.argmax(y_pred,axis=1) scores = classifier.evaluate(x_test, y_test) #print("\n%s: %.2f%%" % (classifier.metrics_names[1], scores[1]*100)) - classifier.save("temp/"+params['name'], save_format='h5') + + + classifier.save(filepath, save_format='h5') + #vizuelizacija u python-u #from ann_visualizer.visualize import ann_viz; #ann_viz(classifier, title="My neural network") - return hist + + return filepath,hist elif(problem_type=='binarni-klasifikacioni'): #print('*************************************************************************binarni') classifier=tf.keras.Sequential() - classifier.add(tf.keras.layers.Dense(units=params['hiddenLayerNeurons'], activation=params['hiddenLayerActivationFunctions'][0],input_dim=x_train.shape[1]))#prvi skriveni + definisanje prethodnog-ulaznog - for i in range(params['hiddenLayers']-1):#ako postoji vise od jednog skrivenog sloja + classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][0],input_dim=x_train.shape[1]))#prvi skriveni + definisanje prethodnog-ulaznog + for i in range(paramsModel['hiddenLayers']-1):#ako postoji vise od jednog skrivenog sloja #print(i) - classifier.add(tf.keras.layers.Dense(units=params['hiddenLayerNeurons'], activation=params['hiddenLayerActivationFunctions'][i+1]))#i-ti skriveni sloj - classifier.add(tf.keras.layers.Dense(units=1, activation=params['outputLayerActivationFunction']))#izlazni sloj + classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][i+1]))#i-ti skriveni sloj + classifier.add(tf.keras.layers.Dense(units=1, activation=paramsModel['outputLayerActivationFunction']))#izlazni sloj - classifier.compile(loss =params["lossFunction"] , optimizer = params['optimizer'] , metrics =params['metrics']) + classifier.compile(loss =paramsModel["lossFunction"] , optimizer = paramsModel['optimizer'] , metrics =paramsModel['metrics']) - history=classifier.fit(x_train, y_train, epochs = params['epochs'],batch_size=params['batchSize']) + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=paramsModel['batchSize']) hist=history.history y_pred=classifier.predict(x_test) y_pred=(y_pred>=0.5).astype('int') @@ -332,25 +338,26 @@ def train(dataset, params, callback): #print("\n%s: %.2f%%" % (classifier.metrics_names[1], scores[1]*100)) #ann_viz(classifier, title="My neural network") - classifier.save("temp/"+params['name'], save_format='h5') - return hist + classifier.save(filepath, save_format='h5') + return filepath,hist elif(problem_type=='regresioni'): classifier=tf.keras.Sequential() - classifier.add(tf.keras.layers.Dense(units=params['hiddenLayerNeurons'], activation=params['hiddenLayerActivationFunctions'][0],input_dim=x_train.shape[1]))#prvi skriveni + definisanje prethodnog-ulaznog - for i in range(params['hiddenLayers']-1):#ako postoji vise od jednog skrivenog sloja + classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][0],input_dim=x_train.shape[1]))#prvi skriveni + definisanje prethodnog-ulaznog + for i in range(paramsModel['hiddenLayers']-1):#ako postoji vise od jednog skrivenog sloja #print(i) - classifier.add(tf.keras.layers.Dense(units=params['hiddenLayerNeurons'], activation=params['hiddenLayerActivationFunctions'][i+1]))#i-ti skriveni sloj + classifier.add(tf.keras.layers.Dense(units=paramsModel['hiddenLayerNeurons'], activation=paramsModel['hiddenLayerActivationFunctions'][i+1]))#i-ti skriveni sloj classifier.add(tf.keras.layers.Dense(units=1)) - classifier.compile(loss =params["lossFunction"] , optimizer = params['optimizer'] , metrics =params['metrics']) + classifier.compile(loss =paramsModel["lossFunction"] , optimizer = paramsModel['optimizer'] , metrics =paramsModel['metrics']) - history=classifier.fit(x_train, y_train, epochs = params['epochs'],batch_size=params['batchSize']) + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=paramsModel['batchSize']) hist=history.history y_pred=classifier.predict(x_test) #print(classifier.evaluate(x_test, y_test)) - return hist + classifier.save(filepath, save_format='h5') + return filepath,hist def roc_auc_score_multiclass(actual_class, pred_class, average = "macro"): #creating a set of all the unique classes using the actual class list -- cgit v1.2.3 From 41bfcba0af1f375349b9fb1935aeb0e0856adff9 Mon Sep 17 00:00:00 2001 From: Nevena Bojovic Date: Sat, 16 Apr 2022 20:05:30 +0200 Subject: Pravi se predictor na ML. --- backend/microservice/api/controller.py | 33 ++++++++++++++++++++++++++++++++- 1 file changed, 32 insertions(+), 1 deletion(-) diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py index d2b8ed2c..95ceccbb 100644 --- a/backend/microservice/api/controller.py +++ b/backend/microservice/api/controller.py @@ -1,4 +1,6 @@ +from dataclasses import dataclass from gc import callbacks +from xmlrpc.client import DateTime import flask from flask import request, jsonify import newmlservice @@ -7,11 +9,27 @@ import pandas as pd import json import requests import config +from datetime import datetime app = flask.Flask(__name__) app.config["DEBUG"] = True app.config["SERVER_NAME"] = config.hostIP - + +@dataclass +class Predictor: + _id : str + username: str + inputs : list + output : str + isPublic: bool + accessibleByLink: bool + dateCreated: DateTime + experimentId: str + modelId: str + h5FileId: str + metrics: list + + class train_callback(tf.keras.callbacks.Callback): def __init__(self, x_test, y_test): self.x_test = x_test @@ -47,6 +65,19 @@ def train(): files = {'file': open(filepath, 'rb')} r=requests.post(url, files=files) fileId=r.text + predictor = Predictor() + predictor._id = "" + predictor.username = paramsModel["username"] + predictor.inputs = paramsExperiment["inputColumns"] + predictor.output = paramsExperiment["outputColumn"] + predictor.isPublic = False + predictor.accessibleByLink = False + predictor.dateCreated = datetime.now() + predictor.experimentId = paramsExperiment["_id"] + predictor.modelId = paramsModel["_id"] + predictor.h5FileId = fileId + + print(result) return jsonify(result) @app.route('/predict', methods = ['POST']) -- cgit v1.2.3 From 838139bbc7bee693cfb8d11e9a29e725bbe36ccb Mon Sep 17 00:00:00 2001 From: TAMARA JERINIC Date: Sat, 16 Apr 2022 20:37:05 +0200 Subject: Prepravka za usaglašavanje sa frontend-om. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- backend/api/api/Controllers/FileController.cs | 1 - backend/microservice/api/controller.py | 25 ++-- backend/microservice/api/newmlservice.py | 6 +- frontend/package-lock.json | 178 +++++++++----------------- frontend/src/app/_data/Model.ts | 4 +- 5 files changed, 83 insertions(+), 131 deletions(-) diff --git a/backend/api/api/Controllers/FileController.cs b/backend/api/api/Controllers/FileController.cs index 6888f1c7..d9494525 100644 --- a/backend/api/api/Controllers/FileController.cs +++ b/backend/api/api/Controllers/FileController.cs @@ -44,7 +44,6 @@ namespace api.Controllers } [HttpPost("h5")] - [Authorize(Roles = "User,Guest")] public async Task> H5Upload([FromForm] IFormFile file) { diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py index 95ceccbb..437690ee 100644 --- a/backend/microservice/api/controller.py +++ b/backend/microservice/api/controller.py @@ -65,19 +65,22 @@ def train(): files = {'file': open(filepath, 'rb')} r=requests.post(url, files=files) fileId=r.text - predictor = Predictor() - predictor._id = "" - predictor.username = paramsModel["username"] - predictor.inputs = paramsExperiment["inputColumns"] - predictor.output = paramsExperiment["outputColumn"] - predictor.isPublic = False - predictor.accessibleByLink = False - predictor.dateCreated = datetime.now() - predictor.experimentId = paramsExperiment["_id"] - predictor.modelId = paramsModel["_id"] - predictor.h5FileId = fileId + predictor = Predictor( + _id = "", + username = paramsModel["username"], + inputs = paramsExperiment["inputColumns"], + output = paramsExperiment["outputColumn"], + isPublic = False, + accessibleByLink = False, + dateCreated = datetime.now(), + experimentId = paramsExperiment["_id"], + modelId = paramsModel["_id"], + h5FileId = fileId, + metrics=[] + ) print(result) + print(predictor) return jsonify(result) @app.route('/predict', methods = ['POST']) diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index e81192ab..585db480 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -122,7 +122,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): for col in paramsExperiment["inputColumns"]: #print(col) data[col]=dataset[col] - output_column = paramsExperiment["columnToPredict"] + output_column = paramsExperiment["outputColumn"] data[output_column] = dataset[output_column] #print(data) @@ -297,8 +297,8 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=paramsModel['batchSize']) hist=history.history - plt.plot(hist['accuracy']) - plt.show() + #plt.plot(hist['accuracy']) + #plt.show() y_pred=classifier.predict(x_test) y_pred=np.argmax(y_pred,axis=1) diff --git a/frontend/package-lock.json b/frontend/package-lock.json index 82cd01e6..488653db 100644 --- a/frontend/package-lock.json +++ b/frontend/package-lock.json @@ -452,7 +452,6 @@ "version": "13.2.5", "resolved": "https://registry.npmjs.org/@angular/compiler-cli/-/compiler-cli-13.2.5.tgz", "integrity": "sha512-Xd8xj2Z0ilA4TJAM/JkTtA1CAa6SuebFsEEvabHCRO5MDvtdsIUP91ADUZIqDHy7qe6Qift/rAVN2PXxT2aaNA==", - "dev": true, "dependencies": { "@babel/core": "^7.17.2", "chokidar": "^3.0.0", @@ -482,7 +481,6 @@ "version": "2.1.2", "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.1.2.tgz", "integrity": "sha512-hoyByceqwKirw7w3Z7gnIIZC3Wx3J484Y3L/cMpXFbr7d9ZQj2mODrirNzcJa+SM3UlpWXYvKV4RlRpFXlWgXg==", - "dev": true, "dependencies": { "@jridgewell/trace-mapping": "^0.3.0" }, @@ -494,7 +492,6 @@ "version": "7.17.5", "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.17.5.tgz", "integrity": "sha512-/BBMw4EvjmyquN5O+t5eh0+YqB3XXJkYD2cjKpYtWOfFy4lQ4UozNSmxAcWT8r2XtZs0ewG+zrfsqeR15i1ajA==", - "dev": true, "dependencies": { "@ampproject/remapping": "^2.1.0", "@babel/code-frame": "^7.16.7", @@ -524,7 +521,6 @@ "version": "6.3.0", "resolved": "https://registry.npmjs.org/semver/-/semver-6.3.0.tgz", "integrity": "sha512-b39TBaTSfV6yBrapU89p5fKekE2m/NwnDocOVruQFS1/veMgdzuPcnOM34M6CwxW8jH/lxEa5rBoDeUwu5HHTw==", - "dev": true, "bin": { "semver": "bin/semver.js" } @@ -533,7 +529,6 @@ "version": "7.17.3", "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.17.3.tgz", "integrity": "sha512-+R6Dctil/MgUsZsZAkYgK+ADNSZzJRRy0TvY65T71z/CR854xHQ1EweBYXdfT+HNeN7w0cSJJEzgxZMv40pxsg==", - "dev": true, "dependencies": { "@babel/types": "^7.17.0", "jsesc": "^2.5.1", @@ -547,7 +542,6 @@ "version": "0.5.7", "resolved": "https://registry.npmjs.org/source-map/-/source-map-0.5.7.tgz", "integrity": "sha1-igOdLRAh0i0eoUyA2OpGi6LvP8w=", - 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"dev": true + "dev": true, + "requires": {} }, "json-schema-traverse": { "version": "0.4.1", @@ -20039,7 +19990,6 @@ "version": "5.0.1", "resolved": "https://registry.npmjs.org/to-regex-range/-/to-regex-range-5.0.1.tgz", "integrity": "sha512-65P7iz6X5yEr1cwcgvQxbbIw7Uk3gOy5dIdtZ4rDveLqhrdJP+Li/Hx6tyK0NEb+2GCyneCMJiGqrADCSNk8sQ==", - "dev": true, "requires": { "is-number": "^7.0.0" } @@ -20108,8 +20058,7 @@ "typescript": { "version": "4.5.5", "resolved": "https://registry.npmjs.org/typescript/-/typescript-4.5.5.tgz", - "integrity": "sha512-TCTIul70LyWe6IJWT8QSYeA54WQe8EjQFU4wY52Fasj5UKx88LNYKCgBEHcOMOrFF1rKGbD8v/xcNWVUq9SymA==", - "dev": true + "integrity": "sha512-TCTIul70LyWe6IJWT8QSYeA54WQe8EjQFU4wY52Fasj5UKx88LNYKCgBEHcOMOrFF1rKGbD8v/xcNWVUq9SymA==" }, "ua-parser-js": { "version": "0.7.31", @@ -20318,7 +20267,8 @@ "version": "3.5.2", "resolved": "https://registry.npmjs.org/ajv-keywords/-/ajv-keywords-3.5.2.tgz", "integrity": "sha512-5p6WTN0DdTGVQk6VjcEju19IgaHudalcfabD7yhDGeA6bcQnmL+CpveLJq/3hvfwd1aof6L386Ougkx6RfyMIQ==", - "dev": true + "dev": true, + "requires": {} }, "json-schema-traverse": { "version": "0.4.1", @@ -20554,7 +20504,8 @@ "version": "8.2.3", "resolved": "https://registry.npmjs.org/ws/-/ws-8.2.3.tgz", "integrity": "sha512-wBuoj1BDpC6ZQ1B7DWQBYVLphPWkm8i9Y0/3YdHjHKHiohOJ1ws+3OccDWtH+PoC9DZD5WOTrJvNbWvjS6JWaA==", - "dev": true + "dev": true, + "requires": {} }, "y18n": { "version": "5.0.8", @@ -20564,8 +20515,7 @@ "yallist": { "version": "4.0.0", "resolved": "https://registry.npmjs.org/yallist/-/yallist-4.0.0.tgz", - "integrity": "sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A==", - "dev": true + "integrity": "sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A==" }, "yaml": { "version": "1.10.2", diff --git a/frontend/src/app/_data/Model.ts b/frontend/src/app/_data/Model.ts index 8a85e296..1af3fe30 100644 --- a/frontend/src/app/_data/Model.ts +++ b/frontend/src/app/_data/Model.ts @@ -73,7 +73,7 @@ export enum LossFunction { HingeLoss = 'hinge_loss', // multi-class classification loss functions CategoricalCrossEntropy = 'categorical_crossentropy', - SparseCategoricalCrossEntropy = 'sparse_categorical_crosentropy', + SparseCategoricalCrossEntropy = 'sparse_categorical_crossentropy', KLDivergence = 'kullback_leibler_divergence', // regression loss functions @@ -95,7 +95,7 @@ export enum LossFunctionBinaryClassification { } export enum LossFunctionMultiClassification { CategoricalCrossEntropy = 'categorical_crossentropy', - SparseCategoricalCrossEntropy = 'sparse_categorical_crosentropy', + SparseCategoricalCrossEntropy = 'sparse_categorical_crossentropy', KLDivergence = 'kullback_leibler_divergence', } -- cgit v1.2.3 From 1816cf8081f345c8e3374fcc5f0e2dbe4914f93d Mon Sep 17 00:00:00 2001 From: Ognjen Cirkovic Date: Sat, 16 Apr 2022 20:43:40 +0200 Subject: Izmenjeno uplodovanje h5 fajlova. --- backend/api/api/.gitignore | 1 + backend/api/api/Controllers/FileController.cs | 19 +++---------------- backend/api/api/api.csproj | 1 + 3 files changed, 5 insertions(+), 16 deletions(-) diff --git a/backend/api/api/.gitignore b/backend/api/api/.gitignore index 17288e4c..3c45979c 100644 --- a/backend/api/api/.gitignore +++ b/backend/api/api/.gitignore @@ -4,6 +4,7 @@ ## Get latest from https://github.com/github/gitignore/blob/master/VisualStudio.gitignore ##Ignore contents for UploadedFiles Folder +PredictorFiles/* UploadedFiles/* !UploadedFiles/Igrannonica TempFiles/* diff --git a/backend/api/api/Controllers/FileController.cs b/backend/api/api/Controllers/FileController.cs index d9494525..c4a14b9a 100644 --- a/backend/api/api/Controllers/FileController.cs +++ b/backend/api/api/Controllers/FileController.cs @@ -44,26 +44,13 @@ namespace api.Controllers } [HttpPost("h5")] - public async Task> H5Upload([FromForm] IFormFile file) + public async Task> H5Upload([FromForm] IFormFile file,[FromForm] string uploaderId) { //get username from jwtToken - string folderName; - - string uploaderId = getUserId(); + string folderName="PredictorFiles"; - if (uploaderId == null) - return BadRequest(); - - if (uploaderId == "") - { - folderName = "TempFiles"; - } - else - { - folderName = "UploadedFiles"; - } //Check filetype @@ -74,7 +61,7 @@ namespace api.Controllers { return BadRequest("Wrong file type"); } - var folderPath = Path.Combine(Directory.GetCurrentDirectory(), folderName, uploaderId); + var folderPath = Path.Combine(Directory.GetCurrentDirectory(), folderName,uploaderId); //Check Directory if (!Directory.Exists(folderPath)) { diff --git a/backend/api/api/api.csproj b/backend/api/api/api.csproj index 7275f67c..306761b4 100644 --- a/backend/api/api/api.csproj +++ b/backend/api/api/api.csproj @@ -21,6 +21,7 @@ + -- cgit v1.2.3 From 3a9bffc6da590fd1a98a0c885d608d40849cffd4 Mon Sep 17 00:00:00 2001 From: Ognjen Cirkovic Date: Sat, 16 Apr 2022 21:48:14 +0200 Subject: Updajtovana poruka koja se salje front end-u. --- backend/api/api/Controllers/ModelController.cs | 3 ++- backend/api/api/api.csproj | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/backend/api/api/Controllers/ModelController.cs b/backend/api/api/Controllers/ModelController.cs index c31b24e1..04c072da 100644 --- a/backend/api/api/Controllers/ModelController.cs +++ b/backend/api/api/Controllers/ModelController.cs @@ -102,7 +102,7 @@ namespace api.Controllers var user = _userService.GetUserByUsername(model.username); if (ChatHub.CheckUser(user._id)) - await _ichat.Clients.Client(ChatHub.Users[user._id]).SendAsync("NotifyEpoch",info.ModelId,info.Stat,model.epochs); + await _ichat.Clients.Client(ChatHub.Users[user._id]).SendAsync("NotifyEpoch",model.name,info.ModelId,info.Stat,model.epochs,info.EpochNum); return Ok(); } @@ -256,6 +256,7 @@ namespace api.Controllers public class Epoch { public string ModelId { get; set; } + public int EpochNum { get; set; } public string Stat { get; set; } } } diff --git a/backend/api/api/api.csproj b/backend/api/api/api.csproj index 306761b4..3d245333 100644 --- a/backend/api/api/api.csproj +++ b/backend/api/api/api.csproj @@ -21,7 +21,7 @@ - + -- cgit v1.2.3 From 66c147bc3154e531cfc78591a7451d904122fc1f Mon Sep 17 00:00:00 2001 From: TAMARA JERINIC Date: Sat, 16 Apr 2022 21:52:40 +0200 Subject: Ispravljeno obaveštavanje backend-a o epohama. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- backend/api/api/Controllers/FileController.cs | 2 +- backend/microservice/api/controller.py | 18 ++++++++++++++---- backend/microservice/api/newmlservice.py | 10 +++++----- 3 files changed, 20 insertions(+), 10 deletions(-) diff --git a/backend/api/api/Controllers/FileController.cs b/backend/api/api/Controllers/FileController.cs index c4a14b9a..68d2ebed 100644 --- a/backend/api/api/Controllers/FileController.cs +++ b/backend/api/api/Controllers/FileController.cs @@ -84,7 +84,7 @@ namespace api.Controllers await file.CopyToAsync(stream); } FileModel fileModel = new FileModel(); - fileModel.type = "h5"; + fileModel.type = ".h5"; fileModel.path = fullPath; fileModel.uploaderId = uploaderId; fileModel.date = DateTime.Now.ToUniversalTime(); diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py index 437690ee..f0f36907 100644 --- a/backend/microservice/api/controller.py +++ b/backend/microservice/api/controller.py @@ -1,4 +1,6 @@ +from cmath import log from dataclasses import dataclass +from distutils.command.upload import upload from gc import callbacks from xmlrpc.client import DateTime import flask @@ -31,16 +33,24 @@ class Predictor: class train_callback(tf.keras.callbacks.Callback): - def __init__(self, x_test, y_test): + def __init__(self, x_test, y_test,modelId): self.x_test = x_test self.y_test = y_test + self.modelId=modelId # def on_epoch_end(self, epoch, logs=None): - print(epoch) + #print('Evaluation: ', self.model.evaluate(self.x_test,self.y_test),"\n") + + #print(epoch) + + #print(logs) + #ml_socket.send(epoch) #file = request.files.get("file") url = config.api_url + "/Model/epoch" - requests.post(url, epoch).text + r=requests.post(url, json={"Stat":str(logs),"ModelId":str(self.modelId),"EpochNum":epoch}).text + + #print(r) #print('Evaluation: ', self.model.evaluate(self.x_test,self.y_test),"\n") #broj parametara zavisi od izabranih metrika loss je default @app.route('/train', methods = ['POST']) @@ -63,7 +73,7 @@ def train(): url = config.api_url + "/file/h5" files = {'file': open(filepath, 'rb')} - r=requests.post(url, files=files) + r=requests.post(url, files=files,data={"uploaderId":paramsExperiment['uploaderId']}) fileId=r.text predictor = Predictor( _id = "", diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index 585db480..a9bce3bb 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -252,7 +252,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): opt=tf.keras.optimizers.RMSprop(learning_rate=params['learningRate']) ###REGULARIZACIJA - #regularisation={'kernelType':'l1 ili l2 ili l1_l2','krenelRate':default=0.01 ili jedna od vrednosti(0.0001,0.001,0.1,1,2,3) ili neka koju je korisnik zadao,'biasType':'','biasRate':'','activityType','activityRate'} + #regularisation={'kernelType':'l1 ili l2 ili l1_l2','kernelRate':default=0.01 ili jedna od vrednosti(0.0001,0.001,0.1,1,2,3) ili neka koju je korisnik zadao,'biasType':'','biasRate':'','activityType','activityRate'} reg=params['regularisation'] ###Kernel @@ -279,7 +279,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): elif(reg['kernelType']=='l1l2'): activityreg=tf.keras.regularizers.l1_l2(l1=reg['activityRate'][0],l2=reg['activityRate'][1]) """ - filepath=os.path.join("temp/",paramsExperiment['_id']+"_"+paramsModel['_id']) + filepath=os.path.join("temp/",paramsExperiment['_id']+"_"+paramsModel['_id']+".h5") if(problem_type=='multi-klasifikacioni'): #print('multi') classifier=tf.keras.Sequential() @@ -294,7 +294,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.compile(loss =paramsModel["lossFunction"] , optimizer = paramsModel['optimizer'] , metrics =paramsModel['metrics']) - history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=paramsModel['batchSize']) + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=paramsModel['batchSize'],callbacks=callback(x_test, y_test,paramsModel['_id'])) hist=history.history #plt.plot(hist['accuracy']) @@ -326,7 +326,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.compile(loss =paramsModel["lossFunction"] , optimizer = paramsModel['optimizer'] , metrics =paramsModel['metrics']) - history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=paramsModel['batchSize']) + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=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') @@ -352,7 +352,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): classifier.compile(loss =paramsModel["lossFunction"] , optimizer = paramsModel['optimizer'] , metrics =paramsModel['metrics']) - history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=paramsModel['batchSize']) + history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=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)) -- cgit v1.2.3 From fcf12f5054cca7e38807531d6b4969e27b86b599 Mon Sep 17 00:00:00 2001 From: Ognjen Cirkovic Date: Sat, 16 Apr 2022 22:09:32 +0200 Subject: Ispravio overwrite guest Tokena na user Token --- frontend/src/app/_services/auth.service.ts | 2 ++ 1 file changed, 2 insertions(+) diff --git a/frontend/src/app/_services/auth.service.ts b/frontend/src/app/_services/auth.service.ts index 92cebe7f..ef340684 100644 --- a/frontend/src/app/_services/auth.service.ts +++ b/frontend/src/app/_services/auth.service.ts @@ -44,6 +44,7 @@ export class AuthService { enableAutoRefresh() { this.lastToken = this.cookie.get('token'); + clearTimeout(this.refresher); let exp = jwtHelper.getTokenExpirationDate(this.lastToken); if (!exp) { exp = new Date(); @@ -51,6 +52,7 @@ export class AuthService { var property = jwtHelper.decodeToken(this.cookie.get('token')); var username = property['name']; if (username != "") { + this.refresher = setTimeout(() => { this.http.post(`${Configuration.settings.apiURL}/auth/renewJwt`, {}, { headers: this.authHeader(), responseType: 'text' }).subscribe((response) => { this.authenticate(response); -- cgit v1.2.3 From 1849a275864cdd7d70e284127360fa211ad470d7 Mon Sep 17 00:00:00 2001 From: Nevena Bojovic Date: Sat, 16 Apr 2022 22:23:02 +0200 Subject: Dodat zahtev addPredictor. --- backend/microservice/api/controller.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py index f0f36907..88e84624 100644 --- a/backend/microservice/api/controller.py +++ b/backend/microservice/api/controller.py @@ -75,6 +75,9 @@ def train(): files = {'file': open(filepath, 'rb')} r=requests.post(url, files=files,data={"uploaderId":paramsExperiment['uploaderId']}) fileId=r.text + m = [] + for attribute, value in result.items(): + m.append({"Name" : attribute, "JsonValue" : jsonify(value)}) predictor = Predictor( _id = "", username = paramsModel["username"], @@ -86,12 +89,12 @@ def train(): experimentId = paramsExperiment["_id"], modelId = paramsModel["_id"], h5FileId = fileId, - metrics=[] + metrics = m ) - - print(result) print(predictor) - return jsonify(result) + url = config.api_url + "/Predictor/add" + r = requests.post(url, json=predictor).text + return r @app.route('/predict', methods = ['POST']) def predict(): -- cgit v1.2.3 From 55b1ee5e4bd96510f8ed2505d157b655a1202a45 Mon Sep 17 00:00:00 2001 From: Danijel Anđelković Date: Sat, 16 Apr 2022 22:53:52 +0200 Subject: Ispravljen bug pri serijalizaciji i deserijalizaciji novog predictora. --- .gitignore | 1 + backend/api/api/Controllers/PredictorController.cs | 1 + backend/microservice/api/controller.py | 56 +++++++++++----------- 3 files changed, 29 insertions(+), 29 deletions(-) diff --git a/.gitignore b/.gitignore index afaf09d3..247afbd9 100644 --- a/.gitignore +++ b/.gitignore @@ -9,3 +9,4 @@ backend/microservice/temp/ backend/microservice/api/__pycache__/ production/app/node_modules/ production/app/dist/ +backend/microservice/api/temp/ diff --git a/backend/api/api/Controllers/PredictorController.cs b/backend/api/api/Controllers/PredictorController.cs index 481334e9..64907dac 100644 --- a/backend/api/api/Controllers/PredictorController.cs +++ b/backend/api/api/Controllers/PredictorController.cs @@ -155,6 +155,7 @@ namespace api.Controllers public async Task> Post([FromBody] Predictor predictor) { var user=_userService.GetUserByUsername(predictor.username); + predictor.dateCreated = DateTime.Now.ToUniversalTime(); var model = _modelService.GetOneModel(predictor.modelId); if (model == null || user==null) return BadRequest("Model not found or user doesnt exist"); diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py index 88e84624..e6515e7b 100644 --- a/backend/microservice/api/controller.py +++ b/backend/microservice/api/controller.py @@ -2,7 +2,6 @@ from cmath import log from dataclasses import dataclass from distutils.command.upload import upload from gc import callbacks -from xmlrpc.client import DateTime import flask from flask import request, jsonify import newmlservice @@ -11,25 +10,24 @@ import pandas as pd import json import requests import config -from datetime import datetime app = flask.Flask(__name__) app.config["DEBUG"] = True app.config["SERVER_NAME"] = config.hostIP -@dataclass -class Predictor: - _id : str - username: str - inputs : list - output : str - isPublic: bool - accessibleByLink: bool - dateCreated: DateTime - experimentId: str - modelId: str - h5FileId: str - metrics: list +#@dataclass +#class Predictor: +# _id : str + # username: str + # inputs : list + # output : str + # isPublic: bool + # accessibleByLink: bool + # dateCreated: DateTime + # experimentId: str + # modelId: str + # h5FileId: str + # metrics: list class train_callback(tf.keras.callbacks.Callback): @@ -77,23 +75,23 @@ def train(): fileId=r.text m = [] for attribute, value in result.items(): - m.append({"Name" : attribute, "JsonValue" : jsonify(value)}) - predictor = Predictor( - _id = "", - username = paramsModel["username"], - inputs = paramsExperiment["inputColumns"], - output = paramsExperiment["outputColumn"], - isPublic = False, - accessibleByLink = False, - dateCreated = datetime.now(), - experimentId = paramsExperiment["_id"], - modelId = paramsModel["_id"], - h5FileId = fileId, - metrics = m - ) + m.append({"Name" : attribute, "JsonValue" : value}) + predictor = { + "_id" : "", + "username" : paramsModel["username"], + "inputs" : paramsExperiment["inputColumns"], + "output" : paramsExperiment["outputColumn"], + "isPublic" : False, + "accessibleByLink" : False, + "experimentId" : paramsExperiment["_id"], + "modelId" : paramsModel["_id"], + "h5FileId" : fileId, + "metrics" : m + } print(predictor) url = config.api_url + "/Predictor/add" r = requests.post(url, json=predictor).text + print(r) return r @app.route('/predict', methods = ['POST']) -- cgit v1.2.3 From f0f9a128076f2f0deae8f597dd780527b54819dd Mon Sep 17 00:00:00 2001 From: TAMARA JERINIC Date: Sun, 17 Apr 2022 17:25:22 +0200 Subject: Izmenjen izgled item-predictor i my-predictors, dodata funkcija za brisanje prediktora u predictors.component.ts. --- .../item-predictor/item-predictor.component.html | 35 ++++++++++++-------- .../my-predictors/my-predictors.component.html | 27 +++++++++------ .../my-predictors/my-predictors.component.ts | 38 ++++++++++++---------- 3 files changed, 59 insertions(+), 41 deletions(-) diff --git a/frontend/src/app/_elements/item-predictor/item-predictor.component.html b/frontend/src/app/_elements/item-predictor/item-predictor.component.html index 7ae26fd3..3199dcc8 100644 --- a/frontend/src/app/_elements/item-predictor/item-predictor.component.html +++ b/frontend/src/app/_elements/item-predictor/item-predictor.component.html @@ -1,26 +1,35 @@
-
- {{predictor.name}} +
+ +
Prediktor
+
-
+
+ Opis

- {{predictor.description}} + {{predictor.description}}

-
- + + Ulazne kolone +
+ +
- +
{{column}}{{column}}
- arrow_downward -

- {{predictor.output}} -

+
+ Izlazna kolona: {{predictor.output}} +
+
+ + +
calendar_today Kreirano{{predictor.dateCreated |date}}
- - +
\ No newline at end of file diff --git a/frontend/src/app/_pages/my-predictors/my-predictors.component.html b/frontend/src/app/_pages/my-predictors/my-predictors.component.html index d38f93e4..31fa786c 100644 --- a/frontend/src/app/_pages/my-predictors/my-predictors.component.html +++ b/frontend/src/app/_pages/my-predictors/my-predictors.component.html @@ -1,16 +1,23 @@ -
-
-
- -
-
- -
- +
+
+
+ +
+
+
+
+ +
+ +
+
+
+
-
+ + diff --git a/frontend/src/app/_pages/my-predictors/my-predictors.component.ts b/frontend/src/app/_pages/my-predictors/my-predictors.component.ts index 17c496fd..4dc5300d 100644 --- a/frontend/src/app/_pages/my-predictors/my-predictors.component.ts +++ b/frontend/src/app/_pages/my-predictors/my-predictors.component.ts @@ -1,7 +1,7 @@ import { Component, OnInit } from '@angular/core'; import Predictor from 'src/app/_data/Predictor'; import { PredictorsService } from 'src/app/_services/predictors.service'; - +import shared from 'src/app/Shared'; @Component({ selector: 'app-my-predictors', templateUrl: './my-predictors.component.html', @@ -12,28 +12,30 @@ export class MyPredictorsComponent implements OnInit { constructor(private predictorsS : PredictorsService) { } ngOnInit(): void { - this.getAllMyPredictors(); - + this.predictorsS.getMyPredictors().subscribe((response) => { + this.predictors = response; + }, (error) => { + if (error.error == "Predictor with...") { + shared.openDialog("Greska", "Greska"); + } + }); } - delete(predictor: Predictor){ - if(window.confirm("IZABRANI MODEL ĆE BITI IZBRISAN")) - { - this.predictorsS.deletePredictor(predictor).subscribe((response) => { - this.getAllMyPredictors(); - }, (error) =>{ - if (error.error == "Predictor with name = {name} deleted") { - alert("Greška pri brisanju modela!"); - } - }); - } - - + deleteThisPredictor(predictor: Predictor): void{ + shared.openYesNoDialog('Brisanje prediktora','Da li ste sigurni da želite da obrišete prediktor?',() => { + this.predictorsS.deletePredictor(predictor).subscribe((response) => { + this.getAllMyPredictors(); + }, (error) =>{ + if (error.error == "Predictor with name = {name} deleted") { + shared.openDialog("Obaveštenje", "Greška prilikom brisanja prediktora."); + } + }); + }); } getAllMyPredictors(): void{ - this.predictorsS.getMyPredictors().subscribe(m => { - this.predictors = m; + this.predictorsS.getMyPredictors().subscribe(p => { + this.predictors = p; }); } -- cgit v1.2.3 From 57f235fc814473f5be947e2b31e7d57f83fcbdd8 Mon Sep 17 00:00:00 2001 From: Danijel Anđelković Date: Sun, 17 Apr 2022 21:52:27 +0200 Subject: Sredio komponentu za notifikacije, tako da moze da se skroluje ako ima puno notifikacija i da mogu da se obrisu notifikacije. Ako stigne notifikacija treniranja za isti model iz prethodne notifikacije, prethodna se prepisuje. --- frontend/src/app/_data/Notification.ts | 1 - .../notifications/notifications.component.html | 16 ++++++++----- .../notifications/notifications.component.ts | 26 +++++++++++++++++++--- 3 files changed, 33 insertions(+), 10 deletions(-) diff --git a/frontend/src/app/_data/Notification.ts b/frontend/src/app/_data/Notification.ts index c505d399..94a3be1d 100644 --- a/frontend/src/app/_data/Notification.ts +++ b/frontend/src/app/_data/Notification.ts @@ -1,5 +1,4 @@ export default class Notification { - _id: string = ''; constructor( public title: string = 'Treniranje u toku...', public id: string = '042', diff --git a/frontend/src/app/_elements/notifications/notifications.component.html b/frontend/src/app/_elements/notifications/notifications.component.html index ef897cfc..3b2f4eaa 100644 --- a/frontend/src/app/_elements/notifications/notifications.component.html +++ b/frontend/src/app/_elements/notifications/notifications.component.html @@ -11,14 +11,18 @@ -
+
-
-

{{notification.title}}

-
-
-
+
+
+

{{notification.title}}

+
+
+
+
+
+
\ No newline at end of file diff --git a/frontend/src/app/_elements/notifications/notifications.component.ts b/frontend/src/app/_elements/notifications/notifications.component.ts index e199f70a..9b460240 100644 --- a/frontend/src/app/_elements/notifications/notifications.component.ts +++ b/frontend/src/app/_elements/notifications/notifications.component.ts @@ -21,13 +21,33 @@ export class NotificationsComponent implements OnInit { this.notifications.push(new Notification(`Obrađen izvor podataka: ${dName}`, dId, 1.0, false)); }); - this.signalRService.hubConnection.on("NotifyEpoch", (epoch: string, mName: string, mId: string, numEpochs) => { - //todo epoch - this.notifications.push(new Notification(`Treniranje modela: ${mName}`, mId, 0.5)); + 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); + if (!existingNotification) + this.notifications.push(new Notification(`Treniranje modela: ${mName}`, mId, progress, true)); + else { + existingNotification.progress = progress; + } + }); + + this.signalRService.hubConnection.on("NotifyModel", (mName: string, mId: string, stat: string, totalEpochs: number, currentEpoch: number) => { + const existingNotification = this.notifications.find(x => x.id === mId) + const progress = ((currentEpoch + 1) / totalEpochs); + if (!existingNotification) + this.notifications.push(new Notification(`Treniranje modela: ${mName}`, mId, progress, true)); + else { + existingNotification.progress = progress; + } }); } else { console.warn("Notifications: No connection!"); } } + removeNotification(notification: Notification) { + this.notifications.splice(this.notifications.indexOf(notification), 1); + } + } -- cgit v1.2.3 From 84b53024a7e0b2c4a0ea34d559678301ad8ee750 Mon Sep 17 00:00:00 2001 From: Nevena Bojovic Date: Sun, 17 Apr 2022 20:36:34 +0200 Subject: Razlicita enkodiranja za kolone ML. --- backend/microservice/api/newmlservice.py | 85 +++++++++++++++++--------------- 1 file changed, 45 insertions(+), 40 deletions(-) diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index a9bce3bb..9951c25f 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -156,48 +156,53 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): # ### Enkodiranje encoding=paramsExperiment["encoding"] - if(encoding=='label'): - encoder=LabelEncoder() - for col in data.columns: - if(data[col].dtype==np.object_): - data[col]=encoder.fit_transform(data[col]) + datafront=dataset.copy() + svekolone=datafront.columns + kategorijskekolone=datafront.select_dtypes(include=['object']).columns + for kolona in svekolone: + if(kolona in kategorijskekolone): + if(encoding=='label'): + encoder=LabelEncoder() + for col in data.columns: + if(data[col].dtype==np.object_): + data[col]=encoder.fit_transform(data[col]) - elif(encoding=='onehot'): - category_columns=[] - for col in data.columns: - if(data[col].dtype==np.object_): - category_columns.append(col) - data=pd.get_dummies(data, columns=category_columns, prefix=category_columns) - - elif(encoding=='ordinal'): - encoder = OrdinalEncoder() - for col in data.columns: - if(data[col].dtype==np.object_): - data[col]=encoder.fit_transform(data[col]) - - elif(encoding=='hashing'): - category_columns=[] - for col in data.columns: - if(data[col].dtype==np.object_): - category_columns.append(col) - encoder=ce.HashingEncoder(cols=category_columns, n_components=len(category_columns)) - encoder.fit_transform(data) - elif(encoding=='binary'): - category_columns=[] - for col in data.columns: - if(data[col].dtype==np.object_): - category_columns.append(col) - encoder=ce.BinaryEncoder(cols=category_columns, return_df=True) - encoder.fit_transform(data) - - elif(encoding=='baseN'): - category_columns=[] - for col in data.columns: - if(data[col].dtype==np.object_): - category_columns.append(col) - encoder=ce.BaseNEncoder(cols=category_columns, return_df=True, base=5) - encoder.fit_transform(data) + elif(encoding=='onehot'): + category_columns=[] + for col in data.columns: + if(data[col].dtype==np.object_): + category_columns.append(col) + data=pd.get_dummies(data, columns=category_columns, prefix=category_columns) + + elif(encoding=='ordinal'): + encoder = OrdinalEncoder() + for col in data.columns: + if(data[col].dtype==np.object_): + data[col]=encoder.fit_transform(data[col]) + + elif(encoding=='hashing'): + category_columns=[] + for col in data.columns: + if(data[col].dtype==np.object_): + category_columns.append(col) + encoder=ce.HashingEncoder(cols=category_columns, n_components=len(category_columns)) + encoder.fit_transform(data) + elif(encoding=='binary'): + category_columns=[] + for col in data.columns: + if(data[col].dtype==np.object_): + category_columns.append(col) + encoder=ce.BinaryEncoder(cols=category_columns, return_df=True) + encoder.fit_transform(data) + + elif(encoding=='baseN'): + category_columns=[] + for col in data.columns: + if(data[col].dtype==np.object_): + category_columns.append(col) + encoder=ce.BaseNEncoder(cols=category_columns, return_df=True, base=5) + encoder.fit_transform(data) # # Input - output # -- cgit v1.2.3 From 4df9512443b2a12c955379860bf759d7d7c9d388 Mon Sep 17 00:00:00 2001 From: TAMARA JERINIC Date: Sun, 17 Apr 2022 23:41:44 +0200 Subject: Uklonjen datum iz treniraj model, broj uzoraka po iteraciji je predstavljen stepenom dvojke, dodat je broj epoha, promenjen naziv funkcije gubitka, dodata ruta. --- .../_elements/model-load/model-load.component.html | 48 ++++++++++++++++------ .../_elements/model-load/model-load.component.ts | 5 +++ frontend/src/app/app-routing.module.ts | 2 + 3 files changed, 42 insertions(+), 13 deletions(-) diff --git a/frontend/src/app/_elements/model-load/model-load.component.html b/frontend/src/app/_elements/model-load/model-load.component.html index f40ea476..85caca0d 100644 --- a/frontend/src/app/_elements/model-load/model-load.component.html +++ b/frontend/src/app/_elements/model-load/model-load.component.html @@ -43,11 +43,7 @@
-
-    - -
+

Parametri treniranja modela:

@@ -58,7 +54,7 @@
- +
- + + + {{newModel.batchSize}} + +
+ +
+
+
+ +
+
+ +
@@ -147,8 +169,8 @@
#{{i+1}}
-
-   -