TensorFlow currently provides a C++ API for registering a custom graph optimizer in Grappler. This project aims to create a modular/plugin-based TensorFlow implementation with C APIs. Plugins will be ...

To quote the TensorFlow website, TensorFlow is an “open source software library for numerical computation using data flow graphs”. What do we mean by “data flow graphs”? Well, that’s the ...

To read networks from TensorFlow framework there is cv::dnn::readNetFromTensorflow method which can work with .pb files with frozen TensorFlow graph. However sometimes it is not enough to have only ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

TensorFlow has released TensorFlow Graph Neural Networks (TF-GNNs), a library designed to make it easy to work with graph-structured data.TF-GNN is a set of TensorFlow building components for ...

Computation Flow Graphs, as illustrated above, are the computational architectures where the nodes represent the Operations (like addition, division, or multiplication) and the edges represent the ...

TF-GNN includes four API components of varying abstraction levels to assist developers with varying machine learning expertise in creating graph models: 1) a data level for representing heterogeneous ...