update registry.py, jenkinsfile_registry

Jenkinsfile_registry

@@ -1,20 +1,13 @@
 pipeline {
     agent {
-       dockerfile {
-			 additionalBuildArgs "--build-arg KAGGLE_USERNAME=${params.KAGGLE_USERNAME} --build-arg KAGGLE_KEY=${params.KAGGLE_KEY} --build-arg CUTOFF=${params.CUTOFF} -t maciejczajka"
-		}
-    }
- parameters {
-        buildSelector(
-          defaultSelector: lastSuccessful(),
-          description: 'Which build to use for copying artifacts for predict',
-          name: 'BUILD_SELECTOR')
+       	image 'maciejczajka'
+       	args '-v /mlruns:/mlruns'
     }
     
     stages {
         stage('Script') {
             steps {
-                copyArtifacts projectName: 's444409-training/main', selector: buildParameter('BUILD_SELECTOR')
+                copyArtifacts projectName: 's444409-training/main'
 		sh 'python3 ./registry.py'
             }
         }

registry.py

@@ -1,9 +1,15 @@
 import mlflow
+import json
+import numpy as np
 logged_model = '/mlruns/12/1c2b9737c0204b0ca825811c35fb6c64/artifacts/s444409'
 
 # Load model as a PyFuncModel.
 loaded_model = mlflow.pyfunc.load_model(logged_model)
 
+with open(f'{logged_model}/input_example.json') as f:
+    data = json.load(f)
+    input_example = np.array([data['inputs'][0]], dtype=np.float32)
+
 # Predict on a Pandas DataFrame.
 import pandas as pd
-print(f'Prediction: {loaded_model.predict(pd.DataFrame(data))}')
+print(f'Prediction: {loaded_model.predict(input_example)}')