What are the parameters For MLflow Project file
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07-12-2022 11:08 AM
Hi! I was just wondering what are the parameters For MLflow Project file?
I'm following this tutorial to create my own MLflow Project: https://docs.databricks.com/applications/mlflow/projects.html
and within this tutorial, the MLproject file looks like this:
name: My Project
conda_env: my_env.yaml
entry_points:
main:
parameters:
data_file: path
regularization: {type: float, default: 0.1}
command: "python train.py -r {regularization} {data_file}"
validate:
parameters:
data_file: path
command: "python validate.py {data_file}"
How did they determine what the parameters are? What exactly are parameters? Are they the parameters from when you do log_param in Mlflow in the notebook?
Please help! Many thanks!
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07-24-2022 02:04 PM
You can refer to MLflow doc for more details.
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09-03-2022 10:28 PM
Hi there @Margie Kale
Does @Prabakar Ammeappin response answer your question? If yes, would you be happy to mark it as best so that other members can find the solution more quickly?
We'd love to hear from you.
Thanks!

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09-04-2022 10:13 PM
I am also encountering this issue. Don't know why its happening.
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09-19-2022 03:32 PM
These parameters are parameters that you will specify when you run the MLflow Project with the mlflow CLI. It lets you parameterize your code, and then pass different parameters to it. How you use them is up to your code. These are not model hyperparameters, of the type you might log with a model.

