MLFlow now uses env variable as default tracking uri (#7457)

* Clarify logger flag

Clarify behavior of boolean values on the logger flag for Trainer.

* Update docs/source/common/trainer.rst

* doc

* MLFlow now uses env variable as default tracking uri

Solves #6894

* Update pytorch_lightning/loggers/mlflow.py

Co-authored-by: thomas chaton <[email protected]>

* changelog

Co-authored-by: SpontaneousDuck <[email protected]>
Co-authored-by: Ethan Harris <[email protected]>
Co-authored-by: Rohit Gupta <[email protected]>
Co-authored-by: Adrian Wälchli <[email protected]>
Co-authored-by: thomas chaton <[email protected]>
Co-authored-by: jirka <[email protected]>

CHANGELOG.md

@@ -41,6 +41,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Changed `model.state_dict()` in `CheckpointConnector` to allow `training_type_plugin` to customize the model's `state_dict()` ([7474](https://github.com/PyTorchLightning/pytorch-lightning/pull/7474))
 
 
+- MLflowLogger now uses the env variable `MLFLOW_TRACKING_URI` as default tracking uri ([7457](https://github.com/PyTorchLightning/pytorch-lightning/pull/7457))
+
+
 ### Deprecated
 
 

pytorch_lightning/loggers/mlflow.py

@@ -16,6 +16,7 @@
 -------------
 """
 import logging
+import os
 import re
 from argparse import Namespace
 from time import time
@@ -85,7 +86,8 @@ def any_lightning_module_function_or_hook(self):
     Args:
         experiment_name: The name of the experiment
         tracking_uri: Address of local or remote tracking server.
-            If not provided, defaults to `file:<save_dir>`.
+            If not provided, defaults to `MLFLOW_TRACKING_URI` environment variable if set, otherwise it falls
+            back to `file:<save_dir>`.
         tags: A dictionary tags for the experiment.
         save_dir: A path to a local directory where the MLflow runs get saved.
             Defaults to `./mlflow` if `tracking_uri` is not provided.
@@ -104,7 +106,7 @@ def any_lightning_module_function_or_hook(self):
     def __init__(
         self,
         experiment_name: str = 'default',
-        tracking_uri: Optional[str] = None,
+        tracking_uri: Optional[str] = os.getenv('MLFLOW_TRACKING_URI'),
         tags: Optional[Dict[str, Any]] = None,
         save_dir: Optional[str] = './mlruns',
         prefix: str = '',