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Deploy paddle model with InferenceService

In this example, we use a trained paddle resnet50 model to classify images by running an inference service with Paddle predictor.

Create the InferenceService

apiVersion: "serving.kserve.io/v1beta1"
kind: "InferenceService"
metadata:
  name: "paddle-resnet50"
spec:
  predictor:
    paddle:
      storageUri: "https://zhouti-mcp-edge.cdn.bcebos.com/resnet50.tar.gz"
Apply the above yaml to create the InferenceService
kubectl apply -f paddle.yaml

Expected Output

inferenceservice.serving.kserve.io/paddle-resnet50 created

Run a Prediction

The first step is to determine the ingress IP and ports and set INGRESS_HOST and INGRESS_PORT

MODEL_NAME=paddle-resnet50
SERVICE_HOSTNAME=$(kubectl get inferenceservice ${MODEL_NAME} -o jsonpath='{.status.url}' | cut -d "/" -f 3)
curl -v -H "Host: ${SERVICE_HOSTNAME}" http://${INGRESS_HOST}:${INGRESS_PORT}/v1/models/${MODEL_NAME}:predict -d @./jay.json

Expected Output

*   Trying 127.0.0.1:80...
* TCP_NODELAY set
* Connected to localhost (127.0.0.1) port 80 (#0)
> POST /v1/models/paddle-resnet50:predict HTTP/1.1
> Host: paddle-resnet50.default.example.com
> User-Agent: curl/7.68.0
> Accept: */*
> Content-Length: 3010209
> Content-Type: application/x-www-form-urlencoded
> Expect: 100-continue
>
* Mark bundle as not supporting multiuse
< HTTP/1.1 100 Continue
* We are completely uploaded and fine
* Mark bundle as not supporting multiuse
< HTTP/1.1 200 OK
< content-length: 23399
< content-type: application/json; charset=UTF-8
< date: Mon, 17 May 2021 03:34:58 GMT
< server: istio-envoy
< x-envoy-upstream-service-time: 511
<
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