| def update_learning(recall,recall_live): | |
| s3_client = boto3.Session(profile_name=None).client('s3') | |
| s3_resource = boto3.resource('s3') | |
| artifact_bucket = 'YOUR ARTIFACT BUCKET ON S3' | |
| if recall>recall_live: | |
| # Push live champion to history | |
| try: | |
| object = s3_client.get_object(Bucket=artifact_bucket, Key='mlflow/'+proj_id+'/live_model_run_history') | |
| live_hist = object['Body'].read().decode("utf-8") | |
| except botocore.exceptions.ClientError as e: | |
| live_hist='' | |
| object = s3_resource.Object(artifact_bucket, 'mlflow/'+proj_id+'/live_model_run_history') | |
| object.put(Body=live_run+" \n"+live_hist) | |
| #Promote active challenger to live champion | |
| object = s3_resource.Object(artifact_bucket, 'mlflow/'+proj_id+'/live_model_run') | |
| object.put(Body=active_run) | |
| print("INFO: New model learnt.") | |
| return 1 | |
| else: | |
| print("INFO: Old model has better performance, keeping it.") | |
| return 0 |
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