fix: pin mlflow<2.19 in 1c_pipeline_with_hyperparameter_sweep to fix …

[Chakradhar886]

Description

Problem
The pipeline_with_hyperparameter_sweep notebook (1c_pipeline_with_hyperparameter_sweep) has been failing since December 16, 2025 with a JobException on the /score_data pipeline step:

Root Cause
Around December 16, 2025, the curated environment sklearn-1.5/labels/latest was updated to include MLflow 2.19+. This version introduced the logged-models API, which is not supported by the AzureML tracking server.

This breaks two things in the pipeline:

Train step: mlflow.autolog() fails to properly log/save the model via the AzureML backend
Predict/score_data step: mlflow.sklearn.load_model() fails to load the model output from the sweep step
The train step appeared to succeed but produced corrupted or incompatible model artifacts, causing the downstream score_data step to fail.

Fix
Pinned mlflow<2.19 at runtime in both component YAML commands:

train.yml — Added pip install 'mlflow<2.19' -q && before python train.py
predict.yml — Added pip install 'mlflow<2.19' -q && before python predict.py
This downgrades MLflow to a compatible version before executing the scripts, restoring compatibility with the AzureML tracking server.

Checklist

• I have read the contribution guidelines.
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• Pull request includes test coverage for the included changes.
• This notebook or file is added to the CODEOWNERS file, pointing to the author or the author's team.

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