replace bash script to docker-compose to build server
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2
train.py
2
train.py
@ -64,7 +64,7 @@ if __name__ == '__main__':
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optimizer = SGD(model.parameters(), lr=learning_rate)
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# set the tracking URI to the model registry
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mlflow.set_tracking_uri('http://127.0.0.1:5000')
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mlflow.set_tracking_uri('http://127.0.0.1:5001')
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mlflow.set_experiment('train_fortune_predict_model')
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# start a new MLflow run
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