Use mlflow variable to set max param length

requirements/pytorch/test.txt

@@ -18,5 +18,6 @@ fastapi  # for `ServableModuleValidator`  # not setting version as re-defined in
 uvicorn  # for `ServableModuleValidator`  # not setting version as re-defined in App
 
 tensorboard >=2.11, <2.21.0  # for `TensorBoardLogger`
+mlflow >=3.0.0, <4.0.0  # for `MLFlowLogger`
 
 torch-tensorrt; platform_system == "Linux" and python_version >= "3.12"

src/lightning/pytorch/loggers/mlflow.py

@@ -233,10 +233,9 @@ def log_hyperparams(self, params: Union[dict[str, Any], Namespace]) -> None:
         params = _flatten_dict(params)
 
         from mlflow.entities import Param
+        from mlflow.utils.validation import MAX_PARAM_VAL_LENGTH
 
-        # Truncate parameter values to 250 characters.
-        # TODO: MLflow 1.28 allows up to 500 characters: https://github.com/mlflow/mlflow/releases/tag/v1.28.0
-        params_list = [Param(key=k, value=str(v)[:250]) for k, v in params.items()]
+        params_list = [Param(key=k, value=str(v)[:MAX_PARAM_VAL_LENGTH]) for k, v in params.items()]
 
         # Log in chunks of 100 parameters (the maximum allowed by MLflow).
         for idx in range(0, len(params_list), 100):

tests/tests_pytorch/loggers/test_mlflow.py

@@ -317,16 +317,17 @@ def test_mlflow_logger_no_synchronous_support(mlflow_mock, tmp_path):
 
 @mock.patch("lightning.pytorch.loggers.mlflow._get_resolve_tags", Mock())
 def test_mlflow_logger_with_long_param_value(mlflow_mock, tmp_path):
-    """Test that long parameter values are truncated to 250 characters."""
+    """Test that long parameter values are truncated using MLflow's MAX_PARAM_VAL_LENGTH."""
+    from mlflow.utils.validation import MAX_PARAM_VAL_LENGTH
 
     def _check_value_length(value, *args, **kwargs):
-        assert len(value) <= 250
+        assert len(value) <= MAX_PARAM_VAL_LENGTH
 
     mlflow_mock.entities.Param.side_effect = _check_value_length
 
     logger = MLFlowLogger("test", save_dir=str(tmp_path))
 
-    params = {"test": "test_param" * 50}
+    params = {"test": "test_param" * 1000}
     logger.log_hyperparams(params)
 
     # assert_called_once_with() won't properly check the parameter value.