add tracking uri
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@ -18,6 +18,7 @@ pipeline {
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sh 'chmod +x tensor.py'
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sh 'python3 tensor.py'
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sh 'rm -rf country_vaccination'
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sh "export MLFLOW_TRACKING_URI=http://172.17.0.1:5000"
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sh 'chmod +x mlflow_model.py'
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sh 'python3 mlflow_model.py'
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}
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@ -4,7 +4,7 @@ import mlflow as mlf
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from tensorflow import keras
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from sklearn.model_selection import train_test_split
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from sklearn.metrics import mean_squared_error as rmse
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from urllib.parse import urlparse
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def create_model(test_size, epochs, batch_size):
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df = pd.read_csv('country_vaccinations.csv').dropna()
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@ -36,9 +36,12 @@ def create_model(test_size, epochs, batch_size):
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return model, rmse_result, signature, input_example
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if __name__ == "__main__":
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mlf.set_tracking_uri("http://172.17.0.1:5000")
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test_size = float(sys.argv[1]) if len(sys.argv) > 1 else 0.2
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epochs = int(sys.argv[2]) if len(sys.argv) > 1 else 100
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batch_size = int(sys.argv[3]) if len(sys.argv) > 1 else 32
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with mlf.start_run():
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mlf.log_param("Test size", test_size)
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mlf.log_param("Epochs", epochs)
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@ -49,7 +52,13 @@ if __name__ == "__main__":
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epochs=epochs,
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batch_size=batch_size,
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)
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mlf.log_metric("RMSE", rmse_result)
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# mlf.keras.log_model(model, "country_vaccination")
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mlf.keras.save_model(model, "country_vaccination", input_example=input_example, signature=signature)
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mlf.set_experiment("s434804")
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tracking_url_type_store = urlparse(mlf.get_tracking_uri()).scheme
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if tracking_url_type_store != "file":
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mlf.keras.log_model(model, "country_vaccinations", registered_model_name="s434804", signature=signature,
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input_example=input_example)
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else:
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mlf.keras.log_model(model, "vaccines_model", signature=signature, input_example=input_example)
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mlf.keras.save_model(model, "country_vaccinations", signature=signature, input_example=input_example)
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