Model Explainers¶
Seldon provides model explanations using its Alibi Open Source library.
We support explainers saved using dill with python 3.7.
Package |
Version |
|---|---|
|
|
We provide an example notebook showing how to deploy an explainer for Tabular, Text and Image models.
Available Methods¶
Seldon Core supports a subset of the methods currently available in Alibi. Presently this the following:
Method |
Explainer Key |
Example |
|---|---|---|
|
||
|
||
|
||
|
||
|
||
|
Creating your explainer¶
For Alibi explainers that need to be trained you should
Use python 3.7 as the Seldon python Alibi explainer wrapper also runs in python 3.7.10 when it loads your explainer.
Follow the Alibi docs for your particular desired explainer. The Seldon Wrapper presently supports: Anchors (Tabular, Text and Image), KernelShap and Integrated Gradients.
Save your explainer to a file called
explainer.dillusing the dill python package and store on a bucket store or PVC in your cluster. We support gcs, s3 (including Minio) or Azure blob.
Explain API¶
For the Seldon Protocol an endpoint path will be exposed for:
http://<ingress-gateway>/seldon/<namespace>/<deployment name>/<predictor name>/api/v1.0/explain
So for example if you deployed:
apiVersion: machinelearning.seldon.io/v1
kind: SeldonDeployment
metadata:
name: income
namespace: seldon
spec:
name: income
annotations:
seldon.io/rest-timeout: "100000"
predictors:
- graph:
children: []
implementation: SKLEARN_SERVER
modelUri: gs://seldon-models/sklearn/income/model-0.23.2
name: classifier
explainer:
type: AnchorTabular
modelUri: gs://seldon-models/sklearn/income/explainer-py36-0.5.2
name: default
replicas: 1
If you were port forwarding to Ambassador on localhost:8003 then the API call would be:
http://localhost:8003/seldon/seldon/income-explainer/default/api/v1.0/explain
The explain method is also supported for tensorflow and v2 kfserving protocols. The full list of endpoint URIs is:
Protocol |
URI |
|---|---|
seldon |
|
tensorflow |
|
kfserving |
|