Home / Books / CODE / 9781789955330_Code / Chapter13 / cloud_classify / server
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README.md

  1. Go to GCP -> VM Instances

  2. Create new instance

    Name: classify-server
Zone: choose appropriate to you, us-central1-a
Generation: first
Machine-type: n1-standard-1
CPU platform: automatic
Hardware configuration: Choose at lease 4 cores and 16GB of RAM
Optionaly: Add GPU
Boot disk: New 10 GB standard persistent disk
Image: Debian GNU/Linux 9 (stretch)
Identity and API access: Compute Engine default service account
Access scopes: Allow default access
Firewall: Allow HTTP traffic

  3. On a web page with a list of VM instances press SSH in the row with instance you created. It will open a new browser window with a command line session.

  4. Install development packages:

    sudo apt-get install git
sudo apt-get install cmake
sudo apt-get install g++
sudo apt-get install libopencv-dev
sudo apt-get install libprotobuf-dev
sudo apt-get install unzip
sudo apt-get install python-pip
sudo apt-get install libopenblas-dev
sudo apt-get install pybind11-dev
pip install pyyaml
pip install typing

  5. Install GCP SDK to the local computer

    1. Go to the https://cloud.google.com/sdk/docs/ URL
    2. Make sure that your system has Python 2 with a release number of Python 2.7.9 or higher.
    3. Download SDK archive
    4. Extract the contents of the file to any location on your file system. If you would like to replace an existing installation, remove the existing google-cloud-sdk directory and extract the archive to the same location.
    5. Run gcloud init to initialize the SDK: 
      ./google-cloud-sdk/bin/gcloud init

      The sample init session :

      You must log in to continue. Would you like to log in (Y/n)?  y
Your browser has been opened to visit:
https://accounts.google.com/o/oauth2/auth?...
Pick cloud project to use: 
[1] hardy-aleph-253219
[2] Create a new project
Please enter numeric choice or text value (must exactly match list item):  1

      Select default choices during the init session.

  6. Go to the Chapter13/python directory and execute export.sh script to download the synset.txt file and and create the model.pt file.

  7. Copy applications source code(the client and server) to the remote instance

    gcloud compute scp --recurse [LOCAL_FILE_PATH] [INSTANCE_NAME]:~/[DEST_PATH]

    Copy model snapshoot to the remote instance:

    gcloud compute scp [LOCAL_FILE_PATH]/model.pt [INSTANCE_NAME]:~/[DEST_PATH]/model
gcloud compute scp [LOCAL_FILE_PATH]/synset.txt [INSTANCE_NAME]:~/[DEST_PATH]/model

    make sure you use same user name on local machine and in the cloud instanse, otherwize copoes will be placed in different directory

  8. Switch to the remote instance, and navigate to the development folder where you placed the application source code:

    cd ~/[DEST_PATH]/server

  9. Clone the http server third-party library:

    git clone https://github.com/yhirose/cpp-httplib third-party/httplib

  10. Clone the PyTorch third-party library:

    cd third-party
wget --no-check-certificate https://download.pytorch.org/libtorch/cu100/libtorch-shared-with-deps-1.2.0.zip
unzip libtorch-shared-with-deps-1.2.0.zip
cd ..

  11. Build PyTorch from sources, because official binaries requires CUDA which can be missed on the server instance:

    cd third-party
git clone https://github.com/pytorch/pytorch.git
cd pytorch/
git checkout v1.2.0
git submodule update --init
mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX=~/dev/server/third-party/pytorch -DUSE_CUDA=OFF -DUSE_CUDNN=OFF -DUSE_OPENMP=ON -DBUILD_TORCH=ON -DUSE_FBGEMM=OFF -DBUILD_PYTHON=OFF
cmake --build . --target install -- -j8

  12. Build our server apllication:

    cd ~/[DEST_PATH]/server
mkdir build
cd build
cmake .. -DCMAKE_PREFIX_PATH=~/dev/server/third-party/pytorch
cmake --build . --target all

  13. Open GCP console and create a firewall rule to allow client requests to the instance:

    1. Go to the VPC network.
    2. Go to the Firewall rules page
    3. In the Create a firewall rule page, enter the following information: 
      Name: classify-server
Target tags: http-server
Actions on match: allow
Source IP ranges: 0.0.0.0/0
Protocol and ports: tcp:8080
    4. Click Create.

  14. Find the instance IP addresses in the GCP console. There are two addresses the internal and external. Got to the: Compute Engine->VM Instances->three dots on selected instance-> View Network details Remember these addresses

  15. On the remove instance start the server application:

    ./classify-server ~/[DEST_PATH]/model/model.pt ~/[DEST_PATH]/model/synset.txt ~/[DEST_PATH]/client/ [internal ip] 8080

  16. On the remote instance update client's source code the upload.js file with the instance external IP address. Change the value of the "url" variable.

  17. On the local computer open the http://[external ip]:8080 URL in the browser.