s444409 prediction

Jenkinsfile-prediction-s444409

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+pipeline {
+    agent {
+        docker {
+			image 'sebastianwalesa/ium:1.0'
+		}
+    }
+ parameters {
+buildSelector(
+          defaultSelector: lastSuccessful(),
+          description: 'Which build to use for copying artifacts for predict',
+          name: 'BUILD_SELECTOR')
+        string(
+            defaultValue: '{\\"inputs\\": [900.0]}',
+            description: 'Input file',
+            name: 'INPUT',
+            trim: true
+        )
+    }
+    
+    stages {
+        stage('Copy Artifacts') {
+            steps {
+                copyArtifacts projectName: 's444409-training/main', selector: buildParameter('BUILD_SELECTOR')
+		sh "echo ${params.INPUT} > input_example.json"
+		sh "python predict.py"
+            }
+        }
+
+        stage('Prediction') {
+            steps {
+		        sh "echo ${params.INPUT} > input_example.json"
+		        sh "python prediction-s444409.py"
+            }
+        }
+    }
+}

prediction-s444409.py

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+import json
+import mlflow
+import sys
+import numpy as np
+
+#input = sys.argv[1]
+
+logged_model = 'mlruns/1/70439eb482b54d56b54b0ecc6f1ca96f/artifacts/s444409'
+loaded_model = mlflow.pyfunc.load_model(logged_model)
+
+
+with open('input_example.json') as f:
+    data = json.load(f)
+    input_example = np.array([data['inputs'][0]], dtype=np.float32)
+
+print(f'Prediction: {loaded_model.predict(input_example)}')