Fix markdownlint errors of docs/tutorials/*.md (#2061)

* Use mdfmt

* Manual fixes

Author: wangkuiyi

docs/tutorials/dev.md

@@ -9,7 +9,6 @@ git clone https://github.com/sql-machine-learning/elasticdl
 cd elasticdl
 ```
 
-
 ## Development Tools in a Docker Image
 
 We prefer to install all building tools in a Docker image.
@@ -18,7 +17,6 @@ We prefer to install all building tools in a Docker image.
 docker build --target dev -t elasticdl:dev -f elasticdl/docker/Dockerfile .
 ```
 
-
 ## Check Code Style
 
 The above Docker image contains pre-commit and hooks.  We can run it as a

docs/tutorials/elasticdl_cloud.md

@@ -1,70 +1,71 @@
 # ElasticDL on Public Cloud
 
-ElasticDL is a Kubernetes-native machine learning framework.  This document explains how to run an ElasticDL job on a public cloud, namely, Google Kubernetes Engine (GKE).
+ElasticDL is a Kubernetes-native machine learning framework.  This document
+explains how to run an ElasticDL job on a public cloud, namely, Google
+Kubernetes Engine (GKE).
 
 ## Configure GKE Environment
 
 ### Create a Project and a Kubernetes Cluster
 
-First, we create a new project for elasticdl in [web console](https://console.cloud.google.com/) and a new Kubernetes cluster under this project.
+First, we create a new project for elasticdl in [web
+console](https://console.cloud.google.com/) and a new Kubernetes cluster under
+this project.
 
 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 SDK](https://cloud.google.com/sdk/install), which includes command-line tools like `gcloud`.
-
+To access GKE, 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.
 
-```
+```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
 ```
 
-Following is an our testing cluster
-
-```
-NAME         LOCATION       MASTER_VERSION  MASTER_IP       MACHINE_TYPE   NODE_VERSION    NUM_NODES  STATUS
-edl-cluster  us-central1-c  1.14.10-gke.36  x.x.x.x         n1-standard-8  1.14.10-gke.36  3          RUNNING
-```
-
 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.
+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
 ```
 
-
 ### Config the Kubernetes Cluster
 
-ElasticDL jobs require pod creation and deletion permissions. Make sure you have granted related permissions to the default or other related service accounts.
+ElasticDL jobs require pod creation and deletion permissions. Make sure you
+have granted related permissions to the default or other related service
+accounts.
 
 ```bash
 kubectl apply -f elasticdl/manifests/elasticdl-rbac.yaml
 ```
 
-ElasticDL supports elastic scheduling, and works well the priority-based scheduling of Kubernetes. We create two customized PriorityClass in the cluster, high and low.
-
+ElasticDL supports elastic scheduling, and works well the priority-based
+scheduling of Kubernetes. We create two customized PriorityClass in the
+cluster, high and low.
 
 high.yaml
 
-```
+```yaml
 apiVersion: scheduling.k8s.io/v1
 kind: PriorityClass
 metadata:
@@ -75,7 +76,7 @@ globalDefault: false
 
 low.yaml
 
-```
+```yaml
 apiVersion: scheduling.k8s.io/v1
 kind: PriorityClass
 metadata:
@@ -84,17 +85,19 @@ value: 1000
 globalDefault: false
 ```
 
-```
+```bash
 kubectl create -f high.yaml
 kubectl create -f low.yaml
 ```
 
-
 ### Mount a Volume for the Kubernetes Cluster
 
-First, we create a [Cloud Filestore](https://cloud.google.com/filestore) instance in web console.
+First, we create a [Cloud Filestore](https://cloud.google.com/filestore)
+instance in web console.
 
-Then we follow the [doc](https://cloud.google.com/filestore/docs/accessing-fileshares) to access fileshares from the Kubernetes cluster.
+Then we follow the
+[doc](https://cloud.google.com/filestore/docs/accessing-fileshares) to access
+fileshares from the Kubernetes cluster.
 
 In this example, we create a persistent value claim named `fileserver-claim`.
 
@@ -104,21 +107,23 @@ In this example, we create a persistent value claim named `fileserver-claim`.
 
 Step 1: We generate MNIST training and evaluation data in RecordIO format.
 
-```
-python elasticdl/python/data/recordio_gen/image_label.py --dataset mnist --records_per_shard 4096 .
+```bash
+python elasticdl/python/data/recordio_gen/image_label.py \
+    --dataset mnist \
+    --records_per_shard 4096 .
 ```
 
-Step 2: We launch a pod which mounts the volume, and use `kubectl cp` command to copy data from local to the volume.
+Step 2: We launch a pod which mounts the volume, and use `kubectl cp` command
+to copy data from local to the volume.
 
-```
+```bash
 kubectl create -f my-pod.yaml
-
 kubectl cp mnist my-pod:/data
 ```
 
 my-pod.yaml
 
-```
+```yaml
 apiVersion: v1
 kind: Pod
 metadata:
@@ -139,15 +144,19 @@ 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) 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:
 
-```
+```bash
 gcloud auth configure-docker
 ```
 
-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.
+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}  \
@@ -180,28 +189,31 @@ python -m elasticdl.python.elasticdl.client train \
 
 To see the status of each pod:
 
-```
+```bash
 kubectl get pods
 ```
 
 To see the loss in worker pod:
 
-```
+```bash
 kubectl logs elasticdl-test-mnist-worker-0 | grep "Loss"
 ```
+
 To see the evaluation metrics in the master pod:
 
-```
+```bash
 kubectl logs elasticdl-test-mnist-master | grep "Evaluation"
 ```
 
 ## Example of Job Fault Tolerance
 
-ElasticDL supports fault tolerance in distributed training. When a worker pod is killed, the training job does not crash and the master pod will try to relaunch a new worker pod.
+ElasticDL supports fault tolerance in distributed training. When a worker pod
+is killed, the training job does not crash and the master pod will try to
+relaunch a new worker pod.
 
 At first, all pods are running:
 
-```
+```text
 elasticdl-test-mnist-master     1/1     Running   0          35s
 elasticdl-test-mnist-ps-0       1/1     Running   0          29s
 elasticdl-test-mnist-ps-1       1/1     Running   0          28s
@@ -213,13 +225,13 @@ elasticdl-test-mnist-worker-3   1/1     Running   0          28s
 
 Then, we delete a worker pod:
 
-```
+```bash
 kubectl delete pod elasticdl-test-mnist-worker-0
 ```
 
 The master pod creates a new worker pod `elasticdl-test-mnist-worker-4` at once.
 
-```
+```text
 NAME                            READY   STATUS    RESTARTS   AGE
 elasticdl-test-mnist-master     1/1     Running   0          51s
 elasticdl-test-mnist-ps-0       1/1     Running   0          45s
@@ -232,11 +244,12 @@ elasticdl-test-mnist-worker-4   1/1     Running   0          6s
 
 ## Example of Elastic Scheduling
 
-After we launch the MNIST training job, we launch another nginx service with high priority in the same cluster.
+After we launch the MNIST training job, we launch another nginx service with
+high priority in the same cluster.
 
 nginx.yaml
 
-```
+```yaml
 apiVersion: apps/v1
 kind: Deployment
 metadata:
@@ -272,13 +285,14 @@ spec:
       restartPolicy: Always
 ```
 
-```
+```bash
 kubectl create -f nginx.yaml
 ```
 
-We will find that some worker pods with low priority are preempted by nginx pods with high priority.
+We will find that some worker pods with low priority are preempted by nginx
+pods with high priority.
 
-```
+```text
 NAME                            READY   STATUS        RESTARTS   AGE
 elasticdl-test-mnist-master     1/1     Running       0          34s
 elasticdl-test-mnist-ps-0       1/1     Running       0          27s
@@ -296,7 +310,7 @@ test-nginx-7585fc5976-ss8pk     0/1     Pending       0          2s
 
 After preemption, the training job still goes on with one worker pod.
 
-```
+```text
 elasticdl-test-mnist-master     1/1     Running   0          61s
 elasticdl-test-mnist-ps-0       1/1     Running   0          54s
 elasticdl-test-mnist-ps-1       1/1     Running   0          54s
@@ -311,16 +325,17 @@ test-nginx-7585fc5976-ckd94     1/1     Running   0          29s
 test-nginx-7585fc5976-ss8pk     1/1     Running   0          29s
 ```
 
-Then, we scale the nginx deployment down to 1 replica. Some cluster resources are freed.
-
+Then, we scale the nginx deployment down to 1 replica. Some cluster resources
+are freed.
 
-```
+```bash
 kubectl scale deployment.v1.apps/test-nginx --replicas=1
 ```
 
-We find that the training job takes over the freed resources, and goes on with 4 worker pods.
+We find that the training job takes over the freed resources, and goes on with
+4 worker pods.
 
-```
+```text
 NAME                            READY   STATUS    RESTARTS   AGE
 elasticdl-test-mnist-master     1/1     Running   0          2m3s
 elasticdl-test-mnist-ps-0       1/1     Running   0          116s

docs/tutorials/elasticdl_on_prem_cluster.md

@@ -2,7 +2,8 @@
 
 ## Environment preparation
 
-You should install ElasticDL first. Please refer to the installation part in [elastic_local](elasticdl_local.md) doc.
+You should install ElasticDL first. Please refer to the installation part in
+[elastic_local](elasticdl_local.md) doc.
 
 Then, build needed images.
 
@@ -13,7 +14,8 @@ bash scripts/travis/build_images.sh
 
 ## Submit job to cluster
 
-The submit command is similar to local mode. The local scripts will be built into a docker image, and pushed to `$DOCKER_HUB_REPO` remote docker hub.
+The submit command is similar to local mode. The local scripts will be built
+into a docker image, and pushed to `$DOCKER_HUB_REPO` remote docker hub.
 
 Following is an exmaple: