The MobileNet example

Run MobileNet tensorflow models as functions.

Prerequisites

If you have not done so already, follow these simple instructions to install Rust and rustwasmc.

Build the WASM bytecode

rustwasmc build --enable-ext

Create FaaS function

Upload the wasm file in the pkg folder to the FaaS. Double check the .wasm file name before you upload.

curl --location --request POST 'https://rpc.ssvm.secondstate.io:8081/api/executables' \
--header 'Content-Type: application/octet-stream' \
--header 'SSVM-Description: mobilenet' \
--data-binary '@pkg/mobilenet_service_lib_bg.wasm'

Returns

{"wasm_id":482,"wasm_sha256":"0x469c28daae7aba392076b4bc5ee3b43ec6d667083d8ae63207bf74b1da03fc26","SSVM_Usage_Key":"00000000-0000-0000-0000-000000000000","SSVM_Admin_Key":"7dxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx0c41"}

Note: You can update this binary with the SSVM_Admin_Key.

curl --location --request PUT 'https://rpc.ssvm.secondstate.io:8081/api/update_wasm_binary/146' \
--header 'Content-Type: application/octet-stream' \
--header 'SSVM_Admin_Key: 7dxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx0c41' \
--data-binary '@pkg/mobilenet_service_lib_bg.wasm'

Test

Make a function call via the web.

curl --location --request POST 'https://rpc.ssvm.secondstate.io:8081/api/run/482/infer' \
--header 'Content-Type: application/octet-stream' \
--data-binary '@test/grace_hopper.jpg'

Local test

You must have Node.js and NPM installed. Install SSVM extensions and dependencies.

$ sudo apt install -y libjpeg-dev libpng-dev
$ wget https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-2.3.0.tar.gz
$ sudo tar -C /usr/local -xzf libtensorflow-cpu-linux-x86_64-2.3.0.tar.gz
$ sudo ldconfig
$ npm i ssvm-extensions

Run the local test on Node.js.

$ cd test
$ node test.js
653 : 0.43212867
Finished post-processing in ... 320.089646ms