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Update TF runtime version in running_pets.md
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research/object_detection/g3doc/running_pets.md

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@@ -208,15 +208,15 @@ For running the training Cloud ML job, we'll configure the cluster to use 5
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training jobs and three parameters servers. The
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configuration file can be found at `object_detection/samples/cloud/cloud.yml`.
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Note: This sample is supported for use with 1.8 runtime version.
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Note: The code sample below is supported for use with 1.9 runtime version.
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To start training and evaluation, execute the following command from the
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`tensorflow/models/research/` directory:
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```bash
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# From tensorflow/models/research/
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gcloud ml-engine jobs submit training `whoami`_object_detection_pets_`date +%m_%d_%Y_%H_%M_%S` \
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--runtime-version 1.8 \
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--runtime-version 1.9 \
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--job-dir=gs://${YOUR_GCS_BUCKET}/model_dir \
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--packages dist/object_detection-0.1.tar.gz,slim/dist/slim-0.1.tar.gz,/tmp/pycocotools/pycocotools-2.0.tar.gz \
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--module-name object_detection.model_main \
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![](img/tensorboard.png)
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Make sure your Tensorboard version is the same minor version as your Tensorflow (1.x)
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You will also want to click on the images tab to see example detections made by
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the model while it trains. After about an hour and a half of training, you can
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expect to see something like this:

research/object_detection/samples/cloud/cloud.yml

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

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