working on lab8

lab8/Jenkinsfile_predict_artifact

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+pipeline {
+    agent {
+        docker {
+            image 's449288/ium:lab8.1'
+        }
+    }
+    parameters {
+        string(
+            defaultValue: '{\\"inputs\\": [[]]}',
+            description: 'Input example in json format',
+            name: 'INPUT'
+        )
+        buildSelector(
+			defaultSelector: lastSuccessful(),
+			description: 'Which build to use for copying artifacts',
+			name: 'BUILD_SELECTOR'
+		)
+    }
+    stages {
+        stage('Stage 1') {
+            steps {
+                echo 'Copying model from s444417-training...' 
+                copyArtifacts projectName: 's444417-training/master', selector: buildParameter('BUILD_SELECTOR')
+                echo 'Model copied'
+                echo 'Making a prediction...'
+                sh 'echo ${params.INPUT} > input_example.json'
+                sh 'python3 predict_s444356.py'
+                echo 'Prediction made'
+            }
+        }
+    }
+}

lab8/Jenkinsfile_predict_registry

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+pipeline {
+    agent {
+        docker {
+            image 's449288/ium:lab8.1'
+            args '-v /mlruns:/mlruns'
+        }
+    }    
+    stages {
+        stage('Stage 1') {
+            steps {
+                echo 'Making a prediction with a model from experiment s444417...'
+                sh "python3 predict_registry.py"
+                echo 'Prediction made'
+            }
+        }
+    }
+}

lab8/predict_artifact.py

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+import mlflow
+import numpy as np
+import json
+
+artifact_path = 'mlruns/1//artifacts/model' #
+model = mlflow.pyfunc.load_model(artifact_path) #
+
+with open(f'{model}/input_example.json') as f:
+    input_example_data = json.load(f)
+
+input_example = np.array() #
+
+print(f'Input example: {input_example}')
+print(f'Model prediction: {model.predict(input_example)}')
+
+
+

lab8/predict_registry.py

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+import mlflow
+import numpy as np
+import json
+
+regsistry_path = '/mlruns/17/ /artifacts/model' #
+model = mlflow.pyfunc.load_model(registry_path) #
+
+with open(f'{model}/input_example.json') as f:
+    input_example_data = json.load(f)
+
+input_example = np.array() #
+
+print(f'Input example: {input_example}')
+print(f'Model prediction: {model.predict(input_example)}')

predict_artifact.py

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+import mlflow
+import numpy as np
+import json
+
+artifact_path = 'mlruns/1//artifacts/model' #
+model = mlflow.pyfunc.load_model(artifact_path) #
+
+with open(f'{model}/input_example.json') as f:
+    input_example_data = json.load(f)
+
+input_example = np.array() #
+
+print(f'Input example: {input_example}')
+print(f'Model prediction: {model.predict(input_example)}')
+
+
+

predict_registry.py

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+import mlflow
+import numpy as np
+import json
+
+regsistry_path = '/mlruns/17/ /artifacts/model' #
+model = mlflow.pyfunc.load_model(registry_path) #
+
+with open(f'{model}/input_example.json') as f:
+    input_example_data = json.load(f)
+
+input_example = np.array() #
+
+print(f'Input example: {input_example}')
+print(f'Model prediction: {model.predict(input_example)}')