RBAC: access denied when request in kubeflow notebooks

Question

I tried the kserve example and faced the problem of RBAC: Access Denied.

1. add user

   $ kubectl -n auth edit cm dex
   

   add example infomation in staticPasswords

       - email: my_email@gmail.com
         hash: my_ps_hash
         userID: "myuserid"
         username: myusername
   

   $ kubectl rollout restart deployment dex -n auth
   

2. add profile for create namespace

   $ vi profile.yaml
   

   apiVersion: kubeflow.org/v1beta1
   kind: Profile
   metadata:
     name: test-namespace
   spec:
     owner:
       kind: User
       name: my_email@gmail.com
     resourceQuotaSpec: {}
   

   kubectl apply -f profile.yaml
   

3. Serving exam model

   kubeflow Central Dashboard - Models - +NEW MODEL SERVER

   apiVersion: "serving.kserve.io/v1beta1"
   kind: "InferenceService"
   metadata:
     annotations:
       isdecar.istio.is/inject: "false"
     name: "sklearn-iris"
   spec:
     predictor:
       sklearn:
         image: "kserve/sklearnserver:v0.9.0"
         storageUri: "gs://kfserving-examples/models/sklearn/1.0/model"
   

   $ kubectl get InferenceService -n test-namespace
   

   NAME                 URL                                                      READY   PREV   LATEST   PREVROLLEDOUTREVISION   LATESTREADYREVISION                          AGE
   sklearn-iris   http://sklearn-iris-test2.test-namespace.example.com   True           100                              sklearn-iris-predictor-default-00001   81m
   

   READY: True

4. Add New Notebook

   kubeflow Central Dashboard - Notebooks - +New Notebook

   and run code

   from kserve import (utils, KServeClient)
   import requests
   import json
   
   sklear_iris_input = dict(instances = [
           [6.8, 2.8, 4.8, 1.4],
           [6.0, 3.4, 4.5, 1.6]
       ])
   
   namespace = utils.get_default_target_namespace()     # Get namespace.  It's worked
   service_name = "sklearn-iris"
   
   kserve = KServeClient()
   isvc_resp = kserve.get(service_name, namespace = namespace)      # It's worked
   # http://sklearn-iris.test-namespace.svc.cluster.local/v1/models/sklearn-iris-test2:predict
   isvc_url = isvc_resp['status']['address']['url'] 
   
   response = requests.post(isvc_url, json = json.dumps(sklear_iris_input))        
   
   print(response.text) 
   

   RBAC: access denied
   

• env:

  kserve: 0.9.0

  kubeflow: 1.6.0

  kubernetes: v1.22.13 and run master node(already disable taint)

Why is this message(RBAC: access denied) occurring?

Your help is of great help to me. Help me!