Voxxed Days Belgrade 2017: Deploying Image Recognition with TensorFlow and Kubernetes

Transcript

1. Enhance! Deploying Image Recognition with TensorFlow and Kubernetes Casey West

   ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 1

2. I am… —Dad, software architect, technical lead, change agent, programmer,

   beverage enthusiast, rock climber, cyclist, acro yoga person… —An Architecture Advocate at Google. I am not… —A data scientist. —An expert in machine learning. ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 2

3. however… ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes

   3

4. I know enough to be dangerous. ! @caseywest @googlecloud @VoxxedBelgrade

   #" #VBD17 #machinelearning #tensorflow #kubernetes 4

5. In 40 minutes you will also know enough to be

   dangerous. ! ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 5

6. Let's get dangerous. ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning

   #tensorflow #kubernetes 6

7. Project Plan —Phase 0: Understand ML Basics —Phase 1: Create

   TensorFlow Serving model —Phase 2: Create TensorFlow Serving client app —Phase 3: Deploy on Kubernetes —Phase 4: Play! ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 7

8. Understand ML Basics ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning

   #tensorflow #kubernetes 8

9. Understand ML Basics ¯\_(ϑ)_/¯ ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17

   #machinelearning #tensorflow #kubernetes 9

10. Training a Model 1. Data 2. Time 3. Procedure !

    @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 10

11. Training a Model 1. Data Historical or available data. !

    @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 11

12. Training a Model 2. Time Iterations you have time to

    make. ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 12

13. Training a Model 3. Procedure Discover data preparation procedures, an

    algorithm to use, and how to configure it. ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 13

14. Training a Model: Steps 1. Get a data set. 2.

    Split it into training and testing data. 3. Train the algorithm. 4. Test the algorithm. 5. Ship it! ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 14

15. Training a Model: Know More in Five Minutes https://www.youtube.com/watch?v=2FmcHiLCwTU —

    Siraj Raval ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 15

16. Image Recognition: Inception v3 https://github.com/tensorflow/models/tree/master/research/inception ! @caseywest @googlecloud @VoxxedBelgrade #"

    #VBD17 #machinelearning #tensorflow #kubernetes 16

17. Serving the model with TensorFlow Serving —Continuous training pipeline —gRPC

    interface —Production ready https://www.tensorflow.org/serving/ ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 17

18. Pre-trained models exist! ! Let's containerize them before they get

    away! ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 18

19. Create a Docker Image: TensorFlow Serving Inception v3 Docker Machine

    docker-machine create \ --driver google \ --google-project goog-caseywest \ --google-zone us-central1-a \ --google-machine-type n1-standard-4 \ docker-machine eval $(docker-machine env docker-machine) ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 19

20. Create a Docker Image: TensorFlow Serving Inception v3 Run developer

    container git clone git@github.com:tensorflow/serving.git cd serving docker build --pull \ -t $USER/tensorflow-serving-devel \ -f tensorflow_serving/tools/docker/Dockerfile.devel . docker run --name=inception_container -it \ $USER/tensorflow-serving-devel ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 20

21. Create a Docker Image: TensorFlow Serving Inception v3 Build in

    the devel the container git clone --recurse-submodules \ https://github.com/tensorflow/serving cd serving/tensorflow ./configure # interactive :-( cd .. bazel build -c opt tensorflow_serving/... ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 21

22. Create a Docker Image: TensorFlow Serving Inception v3 Export inception

    in the devel the container curl -LO http://cwe.st/tf-inception-v3 tar xzf inception-v3-2016-03-01.tar.gz bazel-bin/tensorflow_serving/example/inception_saved_model \ --checkpoint_dir=inception-v3 \ --output_dir=inception-export ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 22

23. Create a Docker Image: TensorFlow Serving Inception v3 Commit and

    deploy container docker commit inception_container \ $USER/inception_serving docker tag $USER/inception_serving \ gcr.io/goog-caseywest/inception gcloud docker -- push \ gcr.io/goog-caseywest/inception ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 23

24. The Machines Have Already Learned Using ML isn't doing ML.

    ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 24

25. Deploy Inception Service on Kubernetes Create a cluster gcloud container

    clusters create \ image-recognition-cluster \ --num-nodes 5 ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 25

26. Let's do it live… ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17

    #machinelearning #tensorflow #kubernetes 26

27. We did it! ! ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17

    #machinelearning #tensorflow #kubernetes 27

28. Takeaways —Training models is hard. —Serving models is kind of

    easy. —gRPC and protobuf have steep learning curves. —therefore, client libraries are challenging. ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 28

29. Want the code? —DM me @caseywest —Email me caseywest@google.com —Try

    a similar tutorial —https://tensorflow.github.io/serving/ serving_inception ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 29

30. Want to try more ML? —TensorFlow —https://www.tensorflow.org/ —MXNet —http://mxnet.io/ —Google

    Cloud Playground —https://cloud.google.com/vision/ ! @caseywest @googlecloud @VoxxedBelgrade #" #VBD17 #machinelearning #tensorflow #kubernetes 30

31. Let's be friends @caseywest ! ! @caseywest @googlecloud @VoxxedBelgrade #"

    #VBD17 #machinelearning #tensorflow #kubernetes 31