Needed to understand how to make seldon work with prepackaged python pickles and servers.
After following instructions from seldonio site for sklearn server, am still unable to get the predefined server models to work.
I have the iris model placed on google cloud storage at location -> gcs://mymodels/sklearn/iris.pkl
I successfully installed seldon-core on gke and ran through a wrapped model example successfully. Now I want to be able to use the pre-packaged servers which can pickup python-pickles from google cloud storage. When I specify the location to the SeldonDeplymentObject , the service never comes up and the pod continues to die.
Here is my SeldonDeployment:
apiVersion: machinelearning.seldon.io/v1alpha2
kind: SeldonDeployment
metadata:
name: sklearniris
spec:
name: seldon_skiris
predictors:
- graph:
children: []
implementation: SKLEARN_SERVER
modelUri: gcs://mymodels/sklearn/iris.pkl
name: classifier
name: default
replicas: 1
What do I setup on gke and gcs to make this work?
The error is in SeldonDeployment line modelUri: gcs://mymodels/sklearn/iris.pkl
. gcs is not the proper path for Google Cloud storage. It should be modelUri: gs://mymodels/sklearn/iris.pkl
Checking the logs for the pod should help see why it continues to die. Describing the pod would also help looking the events for that pod.