[FIXED] 'mlflow' has no attribute 'last_active_run'

Issue

For the first time, it is proceeding mlflow with port 5000.

Testing Mlflow, problem is no attribute last_active_run in mlflow

But, It was an example provided by Mlflow.
link is here mlflow

What is problem and how can I change code?

shell

wget https://raw.githubusercontent.com/mlflow/mlflow/master/examples/sklearn_autolog/utils.py
wget https://raw.githubusercontent.com/mlflow/mlflow/master/examples/sklearn_autolog/pipeline.py

pipeline.py

from pprint import pprint

import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline

import mlflow
from utils import fetch_logged_data


def main():
    # enable autologging
    mlflow.sklearn.autolog()

    # prepare training data
    X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
    y = np.dot(X, np.array([1, 2])) + 3

    # train a model
    pipe = Pipeline([("scaler", StandardScaler()), ("lr", LinearRegression())])
    pipe.fit(X, y)
    run_id = mlflow.last_active_run().info.run_id
    print("Logged data and model in run: {}".format(run_id))

    # show logged data
    for key, data in fetch_logged_data(run_id).items():
        print("\n---------- logged {} ----------".format(key))
        pprint(data)


if __name__ == "__main__":
    main()

utils.py

import mlflow
from mlflow.tracking import MlflowClient


def yield_artifacts(run_id, path=None):
    """Yield all artifacts in the specified run"""
    client = MlflowClient()
    for item in client.list_artifacts(run_id, path):
        if item.is_dir:
            yield from yield_artifacts(run_id, item.path)
        else:
            yield item.path


def fetch_logged_data(run_id):
    """Fetch params, metrics, tags, and artifacts in the specified run"""
    client = MlflowClient()
    data = client.get_run(run_id).data
    # Exclude system tags: https://www.mlflow.org/docs/latest/tracking.html#system-tags
    tags = {k: v for k, v in data.tags.items() if not k.startswith("mlflow.")}
    artifacts = list(yield_artifacts(run_id))
    return {
        "params": data.params,
        "metrics": data.metrics,
        "tags": tags,
        "artifacts": artifacts,
    }

Error message

INFO mlflow.utils.autologging_utils: Created MLflow autologging run with ID '8cc3f4e03b4e417b95a64f1a9a41be63', which will track hyperparameters, performance metrics, model artifacts, and lineage information for the current sklearn workflow
Traceback (most recent call last):
  File "/Users/taein/Desktop/mlflow/pipeline.py", line 33, in <module>
    main()
  File "/Users/taein/Desktop/mlflow/pipeline.py", line 23, in main
    run_id = mlflow.last_active_run().info.run_id
AttributeError: module 'mlflow' has no attribute 'last_active_run'

Thanks for your helping

Solution

It's because of the mlflow version that you mentioned in the comments. mlflow.last_active_run() API was introduced in mlflow 1.25.0 . So you should upgrade the mlflow or you can use the previous version of the code available here.

wget https://raw.githubusercontent.com/mlflow/mlflow/5e2cb3baef544b00a972dff9dd6fb764be20510b/examples/sklearn_autolog/utils.py
wget https://raw.githubusercontent.com/mlflow/mlflow/5e2cb3baef544b00a972dff9dd6fb764be20510b/examples/sklearn_autolog/pipeline.py

Answered By - Matin Zivdar