Update REAME example links for v1alpha1

README.md

@@ -61,7 +61,7 @@ A Suggestion is an algorithm to construct a parameter set. Currently Katib suppo
 ## Components in Katib
 
 Katib consists of several components as shown below. Each component is running on k8s as a deployment.
-Each component communicates with others via GRPC and the API is defined at `pkg/api/api.proto`.
+Each component communicates with others via GRPC and the API is defined at `pkg/api/v1alpha1/api.proto`.
 
 - vizier: main components.
     - vizier-core : API server of vizier.
@@ -78,19 +78,19 @@ Each component communicates with others via GRPC and the API is defined at `pkg/
 
 ## Getting Started
 
-Please see [README.md](./examples/README.md) for more details.
+Please see [README.md](./examples/v1alpha1/README.md) for more details.
 
 ## Web UI
 
 Katib provides a Web UI.
 You can visualize general trend of Hyper parameter space and each training history. You can use
-[random-example](https://github.com/kubeflow/katib/blob/master/examples/random-example.yaml) or
-[other examples](https://github.com/kubeflow/katib/blob/master/examples) to generate a similar UI.
+[random-example](https://github.com/kubeflow/katib/blob/master/examples/v1alpha1/random-example.yaml) or
+[other examples](https://github.com/kubeflow/katib/blob/master/examples/v1alpha1) to generate a similar UI.
 ![katibui](https://user-images.githubusercontent.com/10014831/48778081-a4388b80-ed17-11e8-938b-fc59a5d2e574.gif)
 
 ## API Documentation
 
-Please refer to [api.md](./pkg/api/gen-doc/api.md).
+Please refer to [api.md](./pkg/api/v1alpha1/gen-doc/api.md).
 
 ## Quickstart to run tfjob and pytorch operator jobs in Katib
 
@@ -158,7 +158,7 @@ spec:
 Create this pv after deploying Katib package
 
 ```
-kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/manifests/pv/pv.yaml
+kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/manifests/v1alpha1/pv/pv.yaml
 ```
 
 ### Running examples
@@ -189,21 +189,21 @@ spec:
 If you are not using GKE and you don't have StorageClass for dynamic volume provisioning at your cluster, you have to create pvc and pv
 
 ```
-kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/examples/tfevent-volume/tfevent-pvc.yaml
+kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/examples/v1alpha1/tfevent-volume/tfevent-pvc.yaml
 
-kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/examples/tfevent-volume/tfevent-pv.yaml
+kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/examples/v1alpha1/tfevent-volume/tfevent-pv.yaml
 ```
 
 This is example for tfjob operator
 
 ```
-kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/examples/tfjob-example.yaml
+kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/examples/v1alpha1/tfjob-example.yaml
 ```
 
 This is example for pytorch operator
 
 ```
-kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/examples/pytorchjob-example.yaml
+kubectl create -f https://raw.githubusercontent.com/kubeflow/katib/master/examples/v1alpha1/pytorchjob-example.yaml
 ```
 
 You can check status of StudyJob
@@ -359,7 +359,7 @@ ks delete ${KF_ENV} -c tf-job-operator
 If you create pv for Katib, delete it
 
 ```
-kubectl delete -f https://raw.githubusercontent.com/kubeflow/katib/master/manifests/pv/pv.yaml
+kubectl delete -f https://raw.githubusercontent.com/kubeflow/katib/master/manifests/v1alpha1/pv/pv.yaml
 ```
 
 If you deploy Ambassador, delete it

docs/developer-guide.md

@@ -17,12 +17,12 @@ dep ensure --vendor-only
 You can build all images from source.
 
 ```bash
-./scripts/build.sh
+./scripts/v1alpha1/build.sh
 ```
 
 ## Implement new suggestion algorithm
 
-Suggestion API is defined as GRPC service at `pkg/api/api.proto`. Source code is [here](https://github.com/kubeflow/katib/blob/master/pkg/api/api.proto). You can attach new algorithm easily.
+Suggestion API is defined as GRPC service at `pkg/api/v1alpha1/api.proto`. Source code is [here](https://github.com/kubeflow/katib/blob/master/pkg/api/v1alpha1/api.proto). You can attach new algorithm easily.
 
 - implement suggestion API
 - make k8s service named vizier-suggestion-{ algorithm-name } and expose port 6789

docs/rest-api.md

@@ -1,6 +1,6 @@
-## REST API 
+## REST API
 
-For each RPC service, we define an equivalent HTTP REST API method using [grpc-gateway](https://github.com/grpc-ecosystem/grpc-gateway). The mapping between service and REST API method can be found in this [file](https://github.com/kubeflow/katib/blob/master/pkg/api/api.proto). The mapping includes the URL path, query parameters and request body. You can read more details on the supported methods and binding options at this [link](https://cloud.google.com/service-infrastructure/docs/service-management/reference/rpc/google.api#http)
+For each RPC service, we define an equivalent HTTP REST API method using [grpc-gateway](https://github.com/grpc-ecosystem/grpc-gateway). The mapping between service and REST API method can be found in this [file](https://github.com/kubeflow/katib/blob/master/pkg/api/v1alpha1/api.proto). The mapping includes the URL path, query parameters and request body. You can read more details on the supported methods and binding options at this [link](https://cloud.google.com/service-infrastructure/docs/service-management/reference/rpc/google.api#http)
 
 ## Examples
 

examples/v1alpha1/README.md

@@ -199,7 +199,7 @@ The templates are defined in [ConfigMap](./workerConfigMap.yaml).
 There are two templates: defaultWorkerTemplate.yaml and gpuWorkerTemplate.yaml.
 You can add your template for worker.
 Then you should specify the template in your studyjob spec.
-[This example](/examples/gpu-example.yaml) uses `gpuWorkerTemplate.yaml`.
+[This example](/examples/v1alpha1/gpu-example.yaml) uses `gpuWorkerTemplate.yaml`.
 You can apply it same as other examples.
 ```
 $ kubectl apply -f gpu-example.yaml
@@ -369,7 +369,7 @@ batch2 accuracy=0.8
 Validation-accuracy=0.75
 ```
 The metrics collector will collect all logs of metrics.
-The manifest of metrics collector is also generated from template and defined [here](/manifests/studyjobcontroller/metricsControllerConfigMap.yaml).
+The manifest of metrics collector is also generated from template and defined [here](/manifests/v1alpha1/studyjobcontroller/metricsControllerConfigMap.yaml).
 You can add your template and specify `spec.metricsCollectorSpec.metricsCollectorTemplatePath` in a studyjob manifest.
 
 ### TF Event File Metrics Collector

pkg/api/README.md

@@ -5,9 +5,16 @@ Suggestion service is an API for Suggestion services.
 EarlyStopping service is an API for EarlyStopping services.
 
 ## Documentation
-Please refer to [api.md](./gen-doc/api.md).
+Please refer to the `api.md`:
+ * [v1alpha1 documentation](./v1alpha1/gen-doc/api.md)
+ * [v1alpha2 documentation](./v1alpha2/gen-doc/api.md)
 
 ## Update API and generate documents
-When you want to edit API, please only edit [api.proto](./api.proto) and generate other file from it.
-Documents are also generated from [api.proto](./api.proto) by [protoc-gen-doc](https://github.com/pseudomuto/protoc-gen-doc).
-By [build.sh](./build.sh), you can update every file from api.proto and generate docs.
+When you want to edit the API, please only edit the corresponding `api.proto` and generate other files from it:
+ * [v1alpha1/api.proto](./v1alpha1/api.proto)
+ * [v1alpha2/api.proto](./v1alpha2/api.proto)
+
+Documents are also generated from `api.proto` by [protoc-gen-doc](https://github.com/pseudomuto/protoc-gen-doc).
+Running `build.sh` can update every file from `api.proto` and generate docs:
+ * [v1alpha1/build.sh](./v1alpha1/build.sh)
+ * [v1alpha2/build.sh](./v1alpha2/build.sh)