Firs version o ex.9
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@ -31,15 +31,14 @@ pipeline {
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steps
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steps
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{
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{
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catchError {
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catchError {
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sh 'python3.8 Zadanie_06_and_07_training.py ${BATCH_SIZE} ${EPOCHS}'
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sh 'python3.8 Zadanie_08_and_09_MLflow.py ${BATCH_SIZE} ${EPOCHS}'
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}
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}
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}
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}
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}
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}
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stage('Archive artifacts') {
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stage('Archive artifacts') {
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steps{
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steps{
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archiveArtifacts 'wine_model.h5'
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archiveArtifacts 'my_model/**'
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archiveArtifacts 'my_runs/**'
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}
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}
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}
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}
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}
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}
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@ -8,4 +8,4 @@ entry_points:
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parameters:
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parameters:
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batch_size: {type: int, default: 16}
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batch_size: {type: int, default: 16}
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epochs: {type: int, default: 15}
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epochs: {type: int, default: 15}
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command: "python3 Zadanie_08_MLflow.py {batch_size} {epochs}"
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command: "python3 Zadanie_08_and_09_MLflow.py {batch_size} {epochs}"
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@ -17,6 +17,7 @@ with mlflow.start_run():
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batch_param = int(sys.argv[1]) if len(sys.argv) > 1 else 16
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batch_param = int(sys.argv[1]) if len(sys.argv) > 1 else 16
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epoch_param = int(sys.argv[2]) if len(sys.argv) > 2 else 15
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epoch_param = int(sys.argv[2]) if len(sys.argv) > 2 else 15
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mlflow.set_experiment("s434788")
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mlflow.log_param("batch_size", batch_param)
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mlflow.log_param("batch_size", batch_param)
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mlflow.log_param("epochs", epoch_param)
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mlflow.log_param("epochs", epoch_param)
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@ -69,4 +70,6 @@ with mlflow.start_run():
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print(f"accuracy: {results}")
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print(f"accuracy: {results}")
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mlflow.log_metric("Accuracy", results)
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mlflow.log_metric("Accuracy", results)
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mlflow.keras.save_model(NeuralModel, "my_model")
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