mlflow

biblioteki_ml.py

@@ -5,12 +5,12 @@ import mlflow
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from mlflow.experiments import restore_experiment
 from sklearn.preprocessing import LabelEncoder
 import pandas as pd
 
 # MLFlow
 mlflow.set_tracking_uri("http://172.17.0.1:5000")
+# Niechcący usunąłem eksperyment s444501 i nie mogę go przywrócić dlatego stworzyłem drugi bez literki 's' na początku
 mlflow.set_experiment("444501")
 
 

s444356.Jenkinsfile

@@ -0,0 +1,34 @@
+pipeline {
+    agent {
+        docker {
+	        image 'zadanie'
+	        args '-v /mlruns:/mlruns'
+	    }
+    }
+    parameters {
+        string(
+            defaultValue: '{\\"inputs\\": [[0.51, 0.86], [0.79, 0.79], [0.74, 0.77], [0.66, 0.73], [0.79, 0.47]]}',
+            description: 'Input example',
+            name: 'INPUT'
+        )
+        buildSelector(
+			defaultSelector: lastSuccessful(),
+			description: 'Which build to use for copying artifacts',
+			name: 'BUILD_SELECTOR'
+		)
+    }
+
+    stages {
+        stage('Copy artifacts') {
+            steps {
+                copyArtifacts fingerprintArtifacts: true, projectName: 's444356-training/master', selector: buildParameter('BUILD_SELECTOR')
+            }
+        }
+        stage('Prediction') {
+            steps {
+                sh 'echo ${params.INPUT} > input_example.json'
+                sh 'python s444356.py'
+            }
+        }
+    }
+}

s444356.py

@@ -0,0 +1,12 @@
+import json
+import mlflow
+import numpy as np
+
+model = mlflow.pyfunc.load_model('mlruns/1/4b83e774512444188fb587288818c298/artifacts/model')
+
+with open('input_example.json') as file:
+    data = json.load(file)
+    input_example = np.array([data['inputs'][0]]).reshape(-1, 2)
+    print('Predictions:')
+    for pred in model.predict(input_example):
+        print(pred)