CHART NAME: {{ .Chart.Name }}
CHART VERSION: {{ .Chart.Version }}
APP VERSION: {{ .Chart.AppVersion }}

** Please be patient while the chart is being deployed **

1. Get the TensorFlow Serving URL by running:

  {{- if contains "NodePort" .Values.service.type }}

  export APP_HOST=$(kubectl get nodes --namespace {{ .Release.Namespace }} -o jsonpath="{.items[0].status.addresses[0].address}")
  export APP_PORT=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ template "common.names.fullname" . }} -o jsonpath="{.spec.ports[0].nodePort}")

  {{- else if contains "LoadBalancer" .Values.service.type }}

  NOTE: It may take a few minutes for the LoadBalancer IP to be available.
        Watch the status with: 'kubectl get svc --namespace {{ .Release.Namespace }} -w {{ template "common.names.fullname" . }}'

  export APP_HOST=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ template "common.names.fullname" . }} --template "{{ "{{ range (index .status.loadBalancer.ingress 0) }}{{ . }}{{ end }}" }}")
  export APP_PORT=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ template "common.names.fullname" . }} -o jsonpath="{.spec.ports[0].port}")

  {{- else if contains "ClusterIP" .Values.service.type }}

    export APP_HOST=127.0.0.1
    export APP_PORT=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ template "common.names.fullname" . }} -o jsonpath="{.spec.ports[0].port}")
    kubectl port-forward --namespace {{ .Release.Namespace }} svc/{{ template "common.names.fullname" . }} $APP_PORT:$APP_PORT &

  {{- end }}

2. Test the server with a sample image.

  docker run --rm -it bitnami/tensorflow-resnet bash -c "curl -Lo /tmp/cat.jpg https://tensorflow.org/images/blogs/serving/cat.jpg && resnet_client_cc --server_port=$APP_HOST:$APP_PORT --image_file=/tmp/cat.jpg"

{{ include "tensorflow-resnet.checkRollingTags" . }}
