在 GCS 存储桶上记录来自 MlFlow 的工件

Question

I have a running MlFlow server on GCS VM instance. I have created a bucket to log the artifacts. This is the command I'm running to start the server and for specifying bucket path-

mlflow server --default-artifact-root gs://gcs_bucket/artifacts --host x.x.x.x

But facing this error:

TypeError: stat: path should be string, bytes, os.PathLike or integer, not ElasticNet

Note- The mlflow server is running fine with the specified host alone. The problem is in the way when I'm specifying the storage bucket path. I have given permission of storage api by using these commands:

gcloud auth application-default login
gcloud auth login

Also, on printing the artifact URI, this is what I'm getting:

mlflow.get_artifact_uri()

Output:

gs://gcs_bucket/artifacts/0/122481bf990xxxxxxxxxxxxxxxxxxxxx/artifacts

So in the above path from where this is coming 0/122481bf990xxxxxxxxxxxxxxxxxxxxx/artifacts and why it's not getting auto-created at gs://gcs_bucket/artifacts

After debugging more, why it's not able to get the local path from VM:

And this error I'm getting on VM:

ARNING:root:Malformed experiment 'mlruns'. Detailed error Yaml file './mlruns/mlruns/meta.yaml' does not exist.
Traceback (most recent call last):
 File "/usr/local/lib/python3.6/dist-packages/mlflow/store/tracking/file_store.py", line 197, in list_experiments
   experiment = self._get_experiment(exp_id, view_type)
 File "/usr/local/lib/python3.6/dist-packages/mlflow/store/tracking/file_store.py", line 256, in _get_experiment
   meta = read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)
 File "/usr/local/lib/python3.6/dist-packages/mlflow/utils/file_utils.py", line 160, in read_yaml
   raise MissingConfigException("Yaml file '%s' does not exist." % file_path)
mlflow.exceptions.MissingConfigException: Yaml file './mlruns/mlruns/meta.yaml' does not exist.

Can I get a solution to this and what I'm missing?

Answer 1

I think the main error is from the structure that you want to deploy. For your use case, the structure is suitable that in here . So you miss the URI path which used to store backend metadata. So please install DB SQL(postgres,...) first, then add path to --backend-storage-uri.

In case you just want to use MlFlow like a model registries and store images on gcs. You can use this structure in here

Hope this can help you.