SwiftTFaaS

This repository contains work in progress towards Swift TensorFlow as a Service. The idea is similar to TFaaS with implementation of web server and TF components in Swift. The web framework is based on Vapor.

For TF model we use model produced by SwiftTFExample.

Build notes

In order to start with Vapor you need to build its toolbox.

# NOTE: to build vapor please use Apple/Linux vanila swift toolchain
#       do not use TF toolchain

# download vapor toolbox
git clone https://github.com/vapor/toolbox.git
cd toolbox
# optional you may check out particular branch/tag
git checkout 18.2.2
# build vapor tool
swift build -c release --disable-sandbox --enable-test-discovery --verbose
# copy vapor executable to your favorite OS location
sudo cp .build/release/vapor /usr/local/bin

Now, we can setup a new project (this one is already done):

vapor new <YourProjectName>

and, start coding. To build the code just use

swift build

from your project area.

How to run and access the web server

To run the new code please use

swift run

The server will start on port 8080.

You may add new area Model to your project where you can store your TF models, e.g. when I added model.tf.npy TF model file it appears at a load time

# next the following will appear on your screen
loading weights from: model/model.tf.npy
[ NOTICE ] Server starting on http://127.0.0.1:8080

To place a new request please use

curl http://localhost:8080/inference -H "Content-Type: application/json" -d '{"row":[5.9, 3.0, 4.2, 1.5]}'

The response will look like:

{"request":{"row":[5.0999999046325684,3.2999999523162842,1.7000000476837158,0.5]},"classes":["Iris setosa","Iris versicolor","Iris virginica"],"predictions":[0.84249889850616455,0.091388963162899017,0.066112160682678223]}