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-rw-r--r--backend/api/api/Controllers/DatasetController.cs20
-rw-r--r--backend/api/api/Controllers/ModelController.cs40
-rw-r--r--backend/api/api/Models/Model.cs6
-rw-r--r--backend/api/api/Models/Predictor.cs25
-rw-r--r--backend/api/api/Services/DatasetService.cs12
-rw-r--r--backend/api/api/Services/FillAnEmptyDb.cs13
-rw-r--r--backend/api/api/Services/MlConnectionService.cs13
-rw-r--r--backend/microservice/api/controller.py8
-rw-r--r--backend/microservice/api/newmlservice.py66
9 files changed, 88 insertions, 115 deletions
diff --git a/backend/api/api/Controllers/DatasetController.cs b/backend/api/api/Controllers/DatasetController.cs
index e4741412..849d9884 100644
--- a/backend/api/api/Controllers/DatasetController.cs
+++ b/backend/api/api/Controllers/DatasetController.cs
@@ -144,7 +144,6 @@ namespace api.Controllers
[Authorize(Roles = "User,Guest")]
public async Task<ActionResult<Dataset>> Post([FromBody] Dataset dataset)
{
- Console.WriteLine("PROBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA");
string uploaderId = getUserId();
dataset.uploaderId = uploaderId;
@@ -196,7 +195,7 @@ namespace api.Controllers
string ext = ".csv";
- //nesto
+
//Check Directory
if (!Directory.Exists(folderPath))
@@ -279,19 +278,4 @@ namespace api.Controllers
}
}
-}
-
-/*
-{
- "_id": "",
- "name": "name",
- "description": "description",
- "header" : ["ag","rt"],
- "fileId" : "652",
- "extension": "csb",
- "isPublic" : true,
- "accessibleByLink": true,
- "dateCreated": "dateCreated",
- "lastUpdated" : "proba12"
-}
-*/ \ No newline at end of file
+} \ No newline at end of file
diff --git a/backend/api/api/Controllers/ModelController.cs b/backend/api/api/Controllers/ModelController.cs
index 39eb7830..be30ae6f 100644
--- a/backend/api/api/Controllers/ModelController.cs
+++ b/backend/api/api/Controllers/ModelController.cs
@@ -211,6 +211,8 @@ namespace api.Controllers
return BadRequest("Bad parameters!");*/
model.uploaderId = getUserId();
+ model.dateCreated = DateTime.Now;
+ model.lastUpdated = DateTime.Now;
var existingModel = _modelService.GetOneModel(model.uploaderId, model.name);
@@ -232,6 +234,44 @@ namespace api.Controllers
}
}
+ // POST api/<ModelController>/stealModel
+ [HttpPost("stealModel")]
+ [Authorize(Roles = "User,Guest")]
+ public ActionResult<Model> StealModel([FromBody] Model model)//, bool overwrite)
+ {
+ bool overwrite = false;
+ //username="" ako je GUEST
+ //Experiment e = _experimentService.Get(model.experimentId); umesto 1 ide e.inputColumns.Length TODO!!!!!!!!!!!!!!!!!
+ //model.inputNeurons = e.inputColumns.Length;
+ /*if (_modelService.CheckHyperparameters(1, model.hiddenLayerNeurons, model.hiddenLayers, model.outputNeurons) == false)
+ return BadRequest("Bad parameters!");*/
+
+ model.uploaderId = getUserId();
+ model._id = "";
+ model.dateCreated = DateTime.Now;
+ model.lastUpdated = DateTime.Now;
+ model.isPublic = false;
+
+ var existingModel = _modelService.GetOneModel(model.uploaderId, model.name);
+
+
+ if (existingModel != null && !overwrite && model.validationSize < 1 && model.validationSize > 0)
+ return NotFound($"Model already exisits or validation size is not between 0-1");
+ else
+ {
+ //_modelService.Create(model);
+ //return Ok();
+ if (existingModel == null)
+ _modelService.Create(model);
+ else
+ {
+ _modelService.Replace(model);
+ }
+
+ return CreatedAtAction(nameof(Get), new { id = model._id }, model);
+ }
+ }
+
// PUT api/<ModelController>/{name}
[HttpPut("{name}")]
[Authorize(Roles = "User,Guest")]
diff --git a/backend/api/api/Models/Model.cs b/backend/api/api/Models/Model.cs
index a807316f..bbbf201e 100644
--- a/backend/api/api/Models/Model.cs
+++ b/backend/api/api/Models/Model.cs
@@ -14,18 +14,14 @@ namespace api.Models
public string name { get; set; }
public string description { get; set; }
- //datetime
public DateTime dateCreated { get; set; }
public DateTime lastUpdated { get; set; }
- //proveriti id
- //public string experimentId { get; set; }
//Neural net training
public string type { get; set; }
public string optimizer { get; set; }
public string lossFunction { get; set; }
- //public int inputNeurons { get; set; }
public int hiddenLayers { get; set; }
public string batchSize { get; set; }
public string learningRate { get; set; }
@@ -36,8 +32,6 @@ namespace api.Models
public string[] metrics { get; set; }
public int epochs { get; set; }
- //public bool isTrained { get; set; }
- //public NullValues[] nullValues { get; set; }
public bool randomOrder { get; set; }
public bool randomTestSet { get; set; }
public float randomTestSetDistribution { get; set; }
diff --git a/backend/api/api/Models/Predictor.cs b/backend/api/api/Models/Predictor.cs
index 530257b2..bfe95a0f 100644
--- a/backend/api/api/Models/Predictor.cs
+++ b/backend/api/api/Models/Predictor.cs
@@ -29,27 +29,4 @@ namespace api.Models
}
-}
-
-/**
-* Paste one or more documents here
-
-{
- "_id": {
- "$oid": "625dc348b7856ace8a6f8702"
-
- },
- "uploaderId" : "6242ea59486c664208d4255c",
- "inputs": ["proba",
- "proba2",
- "proba3"
- ],
- "output" : "izlaz",
- "isPublic" : true,
- "accessibleByLink" : true,
- "dateCreated" : "2022-04-11T20:33:26.937+00:00",
- "experimentId" : "Neki id eksperimenta",
- "modelId" : "Neki id eksperimenta",
- "h5FileId" : "Neki id eksperimenta",
- "metrics" : [{ }]
-}*/ \ No newline at end of file
+} \ No newline at end of file
diff --git a/backend/api/api/Services/DatasetService.cs b/backend/api/api/Services/DatasetService.cs
index f38a363b..0b84721e 100644
--- a/backend/api/api/Services/DatasetService.cs
+++ b/backend/api/api/Services/DatasetService.cs
@@ -104,16 +104,6 @@ namespace api.Services
return dataset._id;
}
- /*
-public bool CheckDb()
-{
- Dataset? dataset = null;
- dataset = _dataset.Find(dataset => dataset.username == "igrannonica").FirstOrDefault();
-
- if (dataset != null)
- return false;
- else
- return true;
-}*/
+
}
}
diff --git a/backend/api/api/Services/FillAnEmptyDb.cs b/backend/api/api/Services/FillAnEmptyDb.cs
index 811e723a..cd35dc78 100644
--- a/backend/api/api/Services/FillAnEmptyDb.cs
+++ b/backend/api/api/Services/FillAnEmptyDb.cs
@@ -54,7 +54,7 @@ namespace api.Services
dataset._id = "";
dataset.uploaderId = "000000000000000000000000";
- dataset.name = "Titanik dataset(public)";
+ dataset.name = "Titanik dataset (public)";
dataset.description = "Titanik dataset";
dataset.fileId = _fileService.GetFileId(fullPath);
dataset.extension = ".csv";
@@ -277,6 +277,7 @@ namespace api.Services
model.lossFunction = "sparse_categorical_crossentropy";
model.hiddenLayers = 5;
model.batchSize = "64";
+ model.learningRate = "1";
model.outputNeurons = 0;
model.layers = new[]
{
@@ -368,7 +369,7 @@ namespace api.Services
dataset._id = "";
dataset.uploaderId = "000000000000000000000000";
dataset.name = "IMDB-Movie-Data Dataset (public)";
- dataset.description = "IMDB-Movie-Data Dataset(public)";
+ dataset.description = "IMDB-Movie-Data Dataset (public)";
dataset.fileId = _fileService.GetFileId(fullPath);
dataset.extension = ".csv";
dataset.isPublic = true;
@@ -421,8 +422,8 @@ namespace api.Services
model._id = "";
model.uploaderId = "000000000000000000000000";
- model.name = "IMDB model";
- model.description = "IMDB model";
+ model.name = "IMDB model (public)";
+ model.description = "IMDB model (public)";
model.dateCreated = DateTime.Now;
model.lastUpdated = DateTime.Now;
model.type = "regresioni";
@@ -579,8 +580,8 @@ namespace api.Services
model._id = "";
model.uploaderId = "000000000000000000000000";
- model.name = "Churn model";
- model.description = "Churn model";
+ model.name = "Churn model (public)";
+ model.description = "Churn model (public)";
model.dateCreated = DateTime.Now;
model.lastUpdated = DateTime.Now;
model.type = "binarni-klasifikacioni";
diff --git a/backend/api/api/Services/MlConnectionService.cs b/backend/api/api/Services/MlConnectionService.cs
index 0ecdb1af..6a307e0d 100644
--- a/backend/api/api/Services/MlConnectionService.cs
+++ b/backend/api/api/Services/MlConnectionService.cs
@@ -63,19 +63,6 @@ namespace api.Services
foreach (var connection in ChatHub.getAllConnectionsOfUser(id))
await _ichat.Clients.Client(connection).SendAsync("NotifyDataset",newDataset.name,newDataset._id);
-
- string proba = "";
-
- for (int i = 0; i < newDataset.cMatrix.Length; i++)
- {
- proba = i +" ";
- for (int j = 0; j < newDataset.cMatrix[i].Length; j++)
- proba += newDataset.cMatrix[i][j] + "f, ";
-
- Console.WriteLine(proba);
- proba = "";
- }
-
return;
}
diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py
index 7852b63d..6f483008 100644
--- a/backend/microservice/api/controller.py
+++ b/backend/microservice/api/controller.py
@@ -82,9 +82,6 @@ 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" : value})
predictor = {
"_id" : "",
"uploaderId" : paramsModel["uploaderId"],
@@ -95,13 +92,14 @@ def train():
"experimentId" : paramsExperiment["_id"],
"modelId" : paramsModel["_id"],
"h5FileId" : fileId,
- "metrics" : m,
+ "metrics" : result,
"finalMetrics":finalMetrics
-
}
#print(predictor)
+
url = config.api_url + "/Predictor/add"
r = requests.post(url, json=predictor).text
+
print(r)
return r
diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py
index fd21f8ce..bcff5a33 100644
--- a/backend/microservice/api/newmlservice.py
+++ b/backend/microservice/api/newmlservice.py
@@ -393,14 +393,14 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
macro_averaged_f1=sm.f1_score(y_test, y_pred, average = 'macro')
micro_averaged_f1=sm.f1_score(y_test, y_pred, average = 'micro')
- metrics= {
- "macro_averaged_precision" :float(macro_averaged_precision),
- "micro_averaged_precision" : float(micro_averaged_precision),
- "macro_averaged_recall" : float(macro_averaged_recall),
- "micro_averaged_recall" : float(micro_averaged_recall),
- "macro_averaged_f1" : float(macro_averaged_f1),
- "micro_averaged_f1" : float(micro_averaged_f1)
- }
+ metrics= [
+ {"Name":"macro_averaged_precision", "JsonValue":str(macro_averaged_precision)},
+ {"Name":"micro_averaged_precision" ,"JsonValue":str(micro_averaged_precision)},
+ {"Name":"macro_averaged_recall", "JsonValue":str(macro_averaged_recall)},
+ {"Name":"micro_averaged_recall" ,"JsonValue":str(micro_averaged_recall)},
+ {"Name":"macro_averaged_f1","JsonValue": str(macro_averaged_f1)},
+ {"Name":"micro_averaged_f1", "JsonValue": str(micro_averaged_f1)}
+ ]
#vizuelizacija u python-u
#from ann_visualizer.visualize import ann_viz;
@@ -461,20 +461,20 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
f1 = float(sm.f1_score(y_test,y_pred))
fpr, tpr, _ = sm.roc_curve(y_test,y_pred)
logloss = float(sm.log_loss(y_test, y_pred))
- metrics= {
- "accuracy" : accuracy,
- "precision" : precision,
- "recall" : recall,
- "specificity" : specificity,
- "f1" : f1,
- "tn" : float(tn),
- "fp" : float(fp),
- "fn" : float(fn),
- "tp" : float(tp),
- "fpr" : fpr.tolist(),
- "tpr" : tpr.tolist(),
- "logloss" : logloss
- }
+ metrics= [
+ {"Name":"accuracy" ,"JsonValue": str(accuracy)},
+ {"Name":"precision","JsonValue": str(precision)},
+ {"Name":"recall" , "JsonValue":str(recall)},
+ {"Name":"specificity" ,"JsonValue":str(specificity)},
+ {"Name":"f1" ,"JsonValue": str(f1)},
+ {"Name":"tn" , "JsonValue":str(tn)},
+ {"Name":"fp" , "JsonValue":str(fp)},
+ {"Name":"fn" , "JsonValue":str(fn)},
+ {"Name":"tp" , "JsonValue":str(tp)},
+ {"Name":"fpr" ,"JsonValue": str(fpr.tolist())},
+ {"Name":"tpr" , "JsonValue":str(tpr.tolist())},
+ {"Name":"logloss" , "JsonValue":str(logloss)}
+ ]
return filepath,hist,metrics
@@ -514,12 +514,12 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
history=classifier.fit( x=x_train, y=y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id']),validation_data=(x_val, y_val))
hist=history.history
+
y_pred=classifier.predict(x_test)
#print(classifier.evaluate(x_test, y_test))
classifier.save(filepath, save_format='h5')
-
-
+
mse = float(sm.mean_squared_error(y_test,y_pred))
mae = float(sm.mean_absolute_error(y_test,y_pred))
mape = float(sm.mean_absolute_percentage_error(y_test,y_pred))
@@ -531,14 +531,16 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
n = 40
k = 2
adj_r2 = float(1 - ((1-r2)*(n-1)/(n-k-1)))
- metrics= {"mse" : mse,
- "mae" : mae,
- "mape" : mape,
- "rmse" : rmse,
- "rmsle" : rmsle,
- "r2" : r2,
- "adj_r2" : adj_r2
- }
+ metrics= [
+ {"Name":"mse","JsonValue":str(mse)},
+
+ {"Name":"mae","JsonValue":str(mae)},
+ {"Name":"mape","JsonValue":str( mape)},
+ {"Name":"rmse","JsonValue":str(rmse)},
+ {"Name":"rmsle","JsonValue":str(rmsle)},
+ {"Name":"r2","JsonValue":str( r2)},
+ {"Name":"adj_r2","JsonValue":str(adj_r2)}
+ ]
return filepath,hist,metrics
generated by cgit v1.2.3 (git 2.39.1) at 2025-04-20 00:52:48 +0000