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Tracking MLFlow

If you use MLFlow, you can duplicate Databand metrics to the MLFlow store and maintain data in the MLFlow system as well.

To Integrate MLFlow with Databand

  1. Run the following command to install the integration plugin:
pip install databand[mlflow]
  1. Add the following configuration to your SDK Configuration

# Enable tracking of MLFlow metrics to Databand store.

# Optionally, define a URI for mlflow store; mlflow.get_tracking_uri() is used by default

Task Example

The following example code shows how the logging works.

from dbnd import task
from mlflow import start_run, end_run
from mlflow import log_metric, log_param
from random import random, randint

def mlflow_example():
    # params
    log_param("param1", randint(0, 100))
    log_param("param2", randint(0, 100))
    # metrics
    log_metric("foo1", random())
    log_metric("foo2", random())

Execution Flow

When you run dbnd run mlflow_example, the following happens in the backend:

  1. Databand creates a new DBND context
  2. dbnd_on_pre_init_context hook from dbnd_mlflow is triggered
  3. A new URI is computed to be used by mlflow
    For example: `dbnd://localhost:8081?duplicate_tracking_to=http%253A%252F%252Fmlflow-store%253A80%252F
  4. The new URI is set to be used with mlflow.set_tracking_uri()
  5. mlflow_example task starts:
  6. mlflow.start_run()
  7. mlflow reads entry_points for each installed package and finds:
"dbnd = dbnd_mlflow.tracking_store:get_dbnd_store",
"dbnd+s = dbnd_mlflow.tracking_store:get_dbnd_store",
"databand = dbnd_mlflow.tracking_store:get_dbnd_store",
"databand+s = dbnd_mlflow.tracking_store:get_dbnd_store",
  1. mlflow creates TrackingStoreClient by using the new URI
  2. URI schema instructs to use dbnd_mlflow.tracking_store:get_dbnd_store
    • get_dbnd_store creates dbnd TrackingAPIClient
    • get_dbnd_store creates mlflow tracking store to duplicate tracking to
    • get_dbnd_store returns DatabandStore instance
  3. log_param()/log_metric()
    • calls to DatabandStore
    • calls to TrackingAPIClient
    • calls to mlflow tracking store to duplicate tracking to mlflow.end_run()
  4. mlflow_example ends
  5. dbnd_on_exit_context hook from dbnd_mlflow is triggered
  6. Restore the original mlflow tracking URI.