Update TF runtime version in running_pets.md

research/object_detection/g3doc/running_pets.md

@@ -208,7 +208,7 @@ For running the training Cloud ML job, we'll configure the cluster to use 5
 training jobs and three parameters servers. The
 configuration file can be found at `object_detection/samples/cloud/cloud.yml`.
 
-Note: This sample is supported for use with 1.8 runtime version.
+Note: The code sample below is supported for use with 1.9 runtime version.
 
 To start training and evaluation, execute the following command from the
 `tensorflow/models/research/` directory:
@@ -216,7 +216,7 @@ To start training and evaluation, execute the following command from the
 ```bash
 # From tensorflow/models/research/
 gcloud ml-engine jobs submit training `whoami`_object_detection_pets_`date +%m_%d_%Y_%H_%M_%S` \
-    --runtime-version 1.8 \
+    --runtime-version 1.9 \
     --job-dir=gs://${YOUR_GCS_BUCKET}/model_dir \
     --packages dist/object_detection-0.1.tar.gz,slim/dist/slim-0.1.tar.gz,/tmp/pycocotools/pycocotools-2.0.tar.gz \
     --module-name object_detection.model_main \
@@ -248,6 +248,8 @@ web browser. You should see something similar to the following:
 
 ![](img/tensorboard.png)
 
+Make sure your Tensorboard version is the same minor version as your Tensorflow (1.x)
+
 You will also want to click on the images tab to see example detections made by
 the model while it trains. After about an hour and a half of training, you can
 expect to see something like this:

research/object_detection/samples/cloud/cloud.yml

 trainingInput:
-  runtimeVersion: "1.8"
+  runtimeVersion: "1.9"
   scaleTier: CUSTOM
   masterType: standard_gpu
   workerCount: 5