Model stages

Introduction to MLflow

Weston Bassler

Senior MLOps Engineer

Software envrironments

Diagram of development, staging, and production environments

Introduction to MLflow

MLflow model stages

  • Assigned to model versions

  • Predefined stages:

    • None
    • Staging
    • Production
    • Archived

  • One single stage at a time

Introduction to MLflow

Predefined stages

Predefined Stages

Introduction to MLflow

None

None Stage

Introduction to MLflow

Staging

Staging stage

Introduction to MLflow

Production

Production stage

Introduction to MLflow

Archived

Archived stage

Introduction to MLflow

Transitioning models

transition-ui

# Import MLFlow Client
from mlflow import MlflowClient
client = MlflowClient()


# Transition to Staging
client.transition_model_version_stage(
        name="Unicorn",
        version=3,
        stage="Staging"
    )
Introduction to MLflow

Transition model version staging

# Transition to Staging
client.transition_model_version_stage(name="Unicorn", version=3, stage="Staging")

<ModelVersion: creation_timestamp=1679693470034, current_stage='Staging', 
description=None, last_updated_timestamp=1679699050734, name='Unicorn', 
run_id='a1454f2865e449f8835f38f71e53e547', run_link=None, 
source='./mlruns/1/a1454f2865e449f8835f38f71e53e547/artifacts/model', 
status='READY', status_message=None, tags={}, user_id=None, version=3>
Introduction to MLflow

Registry UI

staging-ui

Introduction to MLflow

Transitioning to production

# Transition to Production
client.transition_model_version_stage(name="Unicorn", version=3, 
                                      stage="Production")

<ModelVersion: creation_timestamp=1679693470034, current_stage='Production', 
description=None, last_updated_timestamp=1679699633297, name='Unicorn', 
run_id='a1454f2865e449f8835f38f71e53e547', run_link=None, 
source='./mlruns/1/a1454f2865e449f8835f38f71e53e547/artifacts/model', 
status='READY', status_message=None, tags={}, user_id=None, version=3>
Introduction to MLflow

Let's practice!

Introduction to MLflow

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