What are the parameters For MLflow Project file

[confusedIntern]

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!

[Prabakar]

You can refer to MLflow doc for more details.

[Vidula]

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!

[Anonymous]

I am also encountering this issue. Don't know why its happening.

[sean_owen]

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.