From 1219f25418625daca0aa0c939712e1d9f53496dd Mon Sep 17 00:00:00 2001
From: Rita Zhang <rita.z.zhang@gmail.com>
Date: Wed, 7 Feb 2018 16:14:38 -0800
Subject: [PATCH] Update apiVersion to kubeflow

---
 5-tfjob/README.md                                    | 12 ++++++------
 6-distributed-tensorflow/README.md                   |  2 +-
 .../solution-chart/templates/deployment.yaml         |  2 +-
 3 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/5-tfjob/README.md b/5-tfjob/README.md
index e956e3b..3f3d574 100644
--- a/5-tfjob/README.md
+++ b/5-tfjob/README.md
@@ -66,7 +66,7 @@ Before going further, let's take a look at what the `TFJob` looks like:
   
 | Field | Type| Description |
 |-------|-----|-------------| 
-| apiVersion | `string` | Versioned schema of this representation of an object. In our case, it's `tensorflow.org/v1alpha1` |
+| apiVersion | `string` | Versioned schema of this representation of an object. In our case, it's `kubeflow.org/v1alpha1` |
 | kind | `string` |  Value representing the REST resource this object represents. In our case it's `TFJob` |
 | metadata | [`ObjectMeta`](https://github.com/kubernetes/community/blob/master/contributors/devel/api-conventions.md#metadata)| Standard object's metadata. |
 | spec | `TFJobSpec` | The actual specification of our TensorFlow job, defined below. |
@@ -125,7 +125,7 @@ spec:
 Here is what the same thing looks like using the new `TFJob` resource:
 
 ```yaml
-apiVersion: tensorflow.org/v1alpha1
+apiVersion: kubeflow.org/v1alpha1
 kind: TFJob
 metadata:
   name: example-tfjob
@@ -212,7 +212,7 @@ Depending on whether or not your cluster has GPU, choose the correct template:
 <summary><strong>CPU Only</strong></summary>  
   
 ```yaml
-apiVersion: tensorflow.org/v1alpha1
+apiVersion: kubeflow.org/v1alpha1
 kind: TFJob
 metadata:
   name: module5-ex1
@@ -234,7 +234,7 @@ spec:
 When using GPU, we need to request for one (or multiple), and the image we are using also needs to be based on TensorFlow's GPU image.
 
 ```yaml
-apiVersion: tensorflow.org/v1alpha1
+apiVersion: kubeflow.org/v1alpha1
 kind: TFJob
 metadata:
   name: module5-ex1-gpu
@@ -393,7 +393,7 @@ This means that when we run a training, all the important data is now stored in
 <summary><strong>Solution</strong></summary>  
 
 ```yaml
-apiVersion: tensorflow.org/v1alpha1
+apiVersion: kubeflow.org/v1alpha1
 kind: TFJob
 metadata:
   name: module5-ex2
@@ -478,7 +478,7 @@ We will also set up the configuration for TensorBoard so that it reads the summa
 <summary><strong>Solution</strong></summary>  
 
 ```yaml
-apiVersion: tensorflow.org/v1alpha1
+apiVersion: kubeflow.org/v1alpha1
 kind: TFJob
 metadata:
   name: module5-ex3
diff --git a/6-distributed-tensorflow/README.md b/6-distributed-tensorflow/README.md
index 63c9fa4..3df7be1 100644
--- a/6-distributed-tensorflow/README.md
+++ b/6-distributed-tensorflow/README.md
@@ -260,7 +260,7 @@ A working code sample is available in [`solution-src/main.py`](./solution-src/ma
 <summary><strong>TFJob's Template</strong></summary>
 
 ```yaml
-apiVersion: tensorflow.org/v1alpha1
+apiVersion: kubeflow.org/v1alpha1
 kind: TFJob
 metadata:
   name: module6-ex1
diff --git a/7-hyperparam-sweep/solution-chart/templates/deployment.yaml b/7-hyperparam-sweep/solution-chart/templates/deployment.yaml
index ca90a9e..1e71e26 100644
--- a/7-hyperparam-sweep/solution-chart/templates/deployment.yaml
+++ b/7-hyperparam-sweep/solution-chart/templates/deployment.yaml
@@ -12,7 +12,7 @@
 # This will result in create 1 TFJob for every pair of learning rate and hidden layer depth
 {{- range $i, $lr := $lrlist }}
 {{- range $j, $nblayers := $nblayerslist }}
-apiVersion: tensorflow.org/v1alpha1
+apiVersion: kubeflow.org/v1alpha1
 kind: TFJob # Each one of our trainings will be a separate TFJob
 metadata:
   name: module7-tf-paint-{{ $i }}-{{ $j }} # We give a unique name to each training