dschonholtz/vectorblox-sdk

Notes about this fork.

This is a fork for the Northeastern Wines Lab: https://ece.northeastern.edu/wineslab/

It is designed to enable using the polarFire board, libero and generate hex files for microchip's libero software with ubuntu 22.04 and 1d Convolutional neural networks.

• Converts a conv-1d model into the conv-2d model format that the polarfire software expects. This allows us to run the optimization software on the given h5 tensorflow model.

• We are currently working on supporting inference of models.

Prerequisites

Ubuntu 16.04 / 18.04 / 20.04 /22.04 are supported If using WSL, ensure you are running from your home directory or have permissions set

Downloading the SDK

There are two options for downloading the sdk:

1. Download an archive.
   Download the zip or tar.gz from https://github.com/Microchip-Vectorblox/VectorBlox-SDK/releases

2. Git clone
   In order to clone it is necessary to have git-lfs installed.To install git-lfs run the following commands on ubuntu:

   curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
   apt update && apt install git-lfs
   git lfs install
   

Install required dependencies (requires sudo permission)

bash install_dependencies.sh

Activate (and installs if needed) Python virtual environment, and sets necessary environment variables

source setup_vars.sh

If during source setup_vars.sh you get an error about "No module named 'mxnet'" chances are git-lfs is not configured correctly.

Run tutorials

Several tutorials are provide to generate CoreVectoBlox compatible Binary Large OBjects (BLOBs)

The tutorials download the networks, convert and optimize the network into openvino xml, and then finally convert the xml into a quantized Vectoblox BLOB with a .vnnx and .hex file extension.

To run the tutorials, follow the below steps.

cd tutorials/{framework}/{network}
bash {network}.sh

A list of tutorials can be found here