mlsync.producers.mlflow package

Submodules

mlsync.producers.mlflow.mlflow_api module

class mlsync.producers.mlflow.mlflow_api.MLFlowAPI(mlflowRoot)

Bases: object

API to interact with MLFlow

getExperiment(experiment_id)

Get the experiment with the given id

Parameters

experiment_id (str) – experiment id

getExperimentRuns(experiment_id, filter_string=None, max_results=50000, order_by=None, page_token=None)

Get the runs with the given experiment id and other filters

Parameters

  • experiment_id (str) – experiment id

  • filter_string (str) – filter string for the query

  • max_results (int) – max number of results to return

  • order_by (str) – order by field

  • page_token (str) – page token

getExperiments()

Get all the experiments

getRunMetric(run_id, metric_key)

Get the experiment with the given id

Parameters

  • run_id (str) – run id, unique for each run

  • metric_key (str) – metric key to get. For example, accuracy

startServer()

Wait until the MLFlow server is up

testUpStatus()

Test the status of the MLFlow server

mlsync.producers.mlflow.mlflow_formatter module

class mlsync.producers.mlflow.mlflow_formatter.MLFlowFormatter(report_format: dict, mlflow_api: MLFlowAPI)

Bases: object

Creates the report format for MLFlow Runs.

Parameters

  • report_format (dict) – The report format to be used.

  • mlflow_api (MLFlowAPI) – The MLFlow API object.

add_alias_table()

Add the alias table to the report

augment_report_format(report_format)

This function will augment over the user provided report format.

Specifically, it will add the following fields:

For experiment:

  • key: Unique identifier for the experiment

  • values: A dictionary of values to be added to the report

For run:

  • key: Unique identifier for the run

  • values: A dictionary of values (provided by the user) to be added to the report

Parameters

report_format (dict) – Report format dict.

format_in(experiments: dict, runs: dict, detailed_metrics: bool) → dict

Convert the MLFlow report to the report format.

Parameters

mlflow_report (dict) – The MLFlow report.

Returns

The report format and the state of the report.

Return type

(dict, dict)

format_out()

Convert the report format to the MLFlow report.

generate_experiment(experiments)

Retain the experiment information

Parameters

  • experiments (dict) – The experiment information from MLFlow

  • experiment_report_format (dict) – The experiment report format

generate_run(runs, detailed_metrics)

Generate the run report

Parameters

  • reports_run (list) – The list of run information from MLFlow

  • run_report_format (dict) – The run report format

generate_run_metrics(report_metric)

Generate the run metrics

Parameters

report_metric (dict) – The metric information from MLFlow

mlsync.producers.mlflow.mlflow_sync module

class mlsync.producers.mlflow.mlflow_sync.MLFlowSync(mlflow_uri, report_format)

Bases: object

Generate the report

pull(detailed_metrics=False)

Generate the MLFlow report based on the given format

push(report)

Push the report to MLFLow

Module contents