update gcloud tutorial according to the new elasticdl client tool (#2117)

* polish gcloud doc

* add gen dataset

Author: QiJune

docs/tutorials/elasticdl_cloud.md

@@ -16,37 +16,17 @@ We will use the project id and cluster name in next steps.
 
 ### Access the Kubernetes Cluster
 
-To access GKE, we need to install [Google Cloud
+To access GKE in a local computer, we need to install [Google Cloud
 SDK](https://cloud.google.com/sdk/install), which includes command-line tools
 like `gcloud`.
 
-Step 1: Set the PROJECT_ID environment variable in shell.
+Luckily, Google Cloud also provides Cloud Shell with `gcloud` installed already.
+In this tutorial, we use Cloud Shell to access the Kubernetes cluster.
+We run the following command in Cloud Shell.
 
 ```bash
 export PROJECT_ID=${your_project_id}
-gcloud config set project ${PROJECT_ID}
-```
-
-Step 2: List clusters info with gcloud, and double check it with web console.
-
-```bash
-gcloud container clusters list
-```
-
-Step 3: Use the command below to generate the corresponding kubeconfig.
-
-```bash
-gcloud container clusters get-credentials edl-cluster --zone us-central1-c
-```
-
-Make sure you have
-[`kubectl`](https://kubernetes.io/docs/tasks/tools/install-kubectl/) available
-locally.
-
-Use the following command to list all the started components.
-
-```bash
-kubectl get all --all-namespaces
+gcloud container clusters get-credentials cluster-1 --zone us-central1-c --project ${PROJECT_ID}
 ```
 
 ### Config the Kubernetes Cluster
@@ -56,6 +36,9 @@ have granted related permissions to the default or other related service
 accounts.
 
 ```bash
+export CODE_PATH=${your_code_dir}
+cd ${CODE_PATH} && git clone https://github.com/sql-machine-learning/elasticdl.git
+cd ${CODE_PATH}/elasticdl
 kubectl apply -f elasticdl/manifests/elasticdl-rbac.yaml
 ```
 
@@ -106,19 +89,25 @@ In this example, we create a persistent value claim named `fileserver-claim`.
 ### Prepare Dataset
 
 Step 1: We generate MNIST training and evaluation data in RecordIO format.
+We provide a script in elasticdl repo.
 
 ```bash
-python elasticdl/python/data/recordio_gen/image_label.py \
-    --dataset mnist \
-    --records_per_shard 4096 .
+cd ${CODE_PATH}/elasticdl
+docker run --rm -it \
+  -v $HOME/.keras/datasets:/root/.keras/datasets \
+  -v $PWD:/work \
+  -w /work elasticdl/elasticdl:dev \
+  bash -c "scripts/gen_dataset.sh data"
 ```
 
+The RecordIO format dataset will generated in the `data` directory.
+
 Step 2: We launch a pod which mounts the volume, and use `kubectl cp` command
-to copy data from local to the volume.
+to copy MNIST dataset from local to the volume.
 
 ```bash
 kubectl create -f my-pod.yaml
-kubectl cp mnist my-pod:/data
+kubectl cp data/mnist my-pod:/data
 ```
 
 my-pod.yaml
@@ -144,22 +133,28 @@ spec:
 
 ### Submit Job
 
-Please refer to [elasticdl_local tutorial](./elasticdl_local.md) to build the
-`elasticdl:ci` image. The difference is that we have to push the image to
-google cloud repo. We use the following command to get the authentication:
+Please refer to [elasticdl_local tutorial](./elasticdl_local.md) for more details.
+The difference is that we have to push the image to google cloud repo.
 
 ```bash
-gcloud auth configure-docker
+pip install elasticdl-client
+
+cd ${CODE_PATH}/elasticdl/model_zoo
+
+elasticdl zoo init
+
+elasticdl zoo build --image=gcr.io/${PROJECT_ID}/elasticdl:mnist .
+
+elasticdl zoo push gcr.io/${PROJECT_ID}/elasticdl:mnist
 ```
 
 We launch a training job with 2 PS pods and 4 worker pods. The master pod and
 PS pods are set with priority, while worker pods are set with low priority. The
 training docker image will be pushed to google cloud repo.
 
 ```bash
-python -m elasticdl.python.elasticdl.client train \
-  --image_base=elasticdl:ci \
-  --docker_image_repository=gcr.io/${PROJECT_ID}  \
+elasticdl train \
+  --image_name=gcr.io/${PROJECT_ID}/elasticdl:mnist \
   --model_zoo=model_zoo \
   --model_def=mnist_functional_api.mnist_functional_api.custom_model \
   --training_data=/data/mnist/train \

scripts/gen_dataset.sh

@@ -0,0 +1,27 @@
+#!/usr/bin/env bash
+# Copyright 2020 The ElasticDL Authors. All rights reserved.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Generate mnist dataset
+DATA_PATH=$1
+
+python elasticdl/python/data/recordio_gen/image_label.py --dataset mnist \
+        --records_per_shard 4096 "$DATA_PATH"
+
+# Generate frappe dataset
+python elasticdl/python/data/recordio_gen/frappe_recordio_gen.py --data /root/.keras/datasets \
+    --output_dir "$DATA_PATH"/frappe
+
+# Generate heart dataset
+python elasticdl/python/data/recordio_gen/heart_recordio_gen.py --data_dir /root/.keras/datasets \
+    --output_dir "$DATA_PATH"/heart