Seldon Core Release 0.4.1¶
A summary of the main contributions to the Seldon Core release 0.4.1.
Black Box Model Explanations¶
By utlizing Seldon’sopen source Model Explanation library Alibi we provide the ability to launch a model and an associated explainer for that model. At present we support the Anchors explanation technique for tabular text and image examples.
An example SeldonDeployment for an image model with associated explainer is shown below:
apiVersion: machinelearning.seldon.io/v1alpha2 kind: SeldonDeployment metadata: name: image spec: annotations: seldon.io/rest-read-timeout: "10000000" seldon.io/grpc-read-timeout: "10000000" seldon.io/grpc-max-message-size: "1000000000" name: image predictors: - graph: children:  implementation: TENSORFLOW_SERVER modelUri: gs://seldon-models/tfserving/imagenet/model name: classifier endpoint: type: GRPC parameters: - name: model_name type: STRING value: classifier - name: model_input type: STRING value: input_image - name: model_output type: STRING value: predictions/Softmax:0 engineResources: requests: memory: 1Gi explainer: type: anchor_images modelUri: gs://seldon-models/tfserving/imagenet/explainer name: default replicas: 1
The Tensorflow model has a
anchor_images explainer associated with it. An example input showing a persian cat along with an example explanation for that image showing the segment of the image the model focused on for providing the classifcation result can be seen below.
We now use Jenkins X as our project CICD platform.
We are available on the RedHat Container Catalog. Update to 0.4.1 soon.