Using ML Flow>train projects remote throwing error for conda env path

Start with notebooks/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-projects-remote/train-projects-remote.ipynb and the failing mlflow.projects.run call in cell 15. Trace the Azure ML backend handling of the Project object and its conda environment lookup. Done means the remote experiment runs without the conda_env_path AttributeError.

When executing the train-projects-remote notebook in VS Code it throws and error when you try to run the experiment.
AttributeError: 'Project' object has no attribute 'conda_env_path'

Output exceeds the size limit. Open the full output data in a text editor

AttributeError Traceback (most recent call last)
/home/brcampb/projects/ml/notebooks/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-projects-remote/train-projects-remote.ipynb Cell 15 in <cell line: 1>()
----> 1 remote_mlflow_run = mlflow.projects.run(uri=".",
2 parameters={"alpha":0.3},
3 backend = "azureml",
4 backend_config = backend_config,
5 synchronous=True)

File ~/miniconda3/envs/azureml/lib/python3.8/site-packages/mlflow/projects/init.py:331, in run(uri, entry_point, version, parameters, docker_args, experiment_name, experiment_id, backend, backend_config, use_conda, storage_dir, synchronous, run_id, run_name, env_manager)
325 backend_config_dict[MLFLOW_LOCAL_BACKEND_RUN_ID_CONFIG] = run_id
327 experiment_id = _resolve_experiment_id(
328 experiment_name=experiment_name, experiment_id=experiment_id
329 )
--> 331 submitted_run_obj = _run(
332 uri=uri,
333 experiment_id=experiment_id,
334 entry_point=entry_point,
335 version=version,
336 parameters=parameters,
337 docker_args=docker_args,
338 backend_name=backend,
339 backend_config=backend_config_dict,
340 env_manager=env_manager,
341 storage_dir=storage_dir,
...
---> 96 if mlproject.conda_env_path:
97 _logger.info(_CONSOLE_MSG.format("Creating remote conda environment for project using MLproject"))
98 environment = Environment.from_conda_specification(name="environment", file_path=mlproject.conda_env_path)

AttributeError: 'Project' object has no attribute 'conda_env_path'