Back-end (run.py): The Flask server application, which: Loads the deep learning PyTorch model on start; Receives base64 encoded drawing; Preprocesses the drawing; Passes preprocessed drawing to the ...

We tested the code with PyTorch 1.10 and Deep Graph Library (DGL). Follow the instructions on the official websites for further details. data : folder with dataset and utilities to generate datasets ...

The IBM team is combining three techniques within PyTorch – graph fusion, kernel optimizations, and parallel tensors – to achieve faster inference speeds.

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

This document serves as user manual for HydraGNN, a scalable graph neural network (GNN) architecture that allows for a simultaneous prediction of multiple target properties using multi-task learning ...