MLmodel file
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@ -6,3 +6,4 @@ metrics.tsv
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plot.png
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my_runs
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mlruns
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my_model
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@ -34,11 +34,11 @@ pipeline {
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sh 'rm -rf my_model'
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sh 'chmod +x dlgssdpytorch.py'
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sh 'python3 ./dlgssdpytorch.py $PARAMETRY'
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//sh 'chmod +x train_mlflow.py'
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sh 'chmod +x train_mlflow.py'
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//sh 'chmod +x generate_MLmodel.py'
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//sh 'python3 ./generate_MLmodel.py'
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//sh 'mlflow ./train_mlflow.py'
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//sh 'mlflow run .'
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sh 'mlflow run .'
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}
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}
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}
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@ -20,13 +20,13 @@ class LayerLinearRegression(nn.Module):
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# Now it only takes a call to the layer to make predictions
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return self.linear(x)
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parser = argparse.ArgumentParser(description='Program do uczenia modelu')
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parser.add_argument('-l', '--lr', type=float, default=1e-3, help="Współczynik uczenia (lr)", required=False)
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parser.add_argument('-e', '--epochs', type=int, default=100, help="Liczba epok", required=False)
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args = parser.parse_args()
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description='Program do uczenia modelu')
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parser.add_argument('-l', '--lr', type=float, default=1e-3, help="Współczynik uczenia (lr)", required=False)
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parser.add_argument('-e', '--epochs', type=int, default=100, help="Liczba epok", required=False)
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args = parser.parse_args()
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lr = args.lr
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n_epochs = args.epochs
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mlflow.set_experiment("s426206")
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