instead of constructing the entire graph as a single opaque object and evaluating it all at once. This so-called “eager execution mode,” provided as an option in older versions of TensorFlow ...

Everything we know about Google's AI builder TensorFlow uses a dataflow graph to represent computations. It shares this space with another open-source machine-learning framework called PyTorch.

Among the innovations that power the popular open source TensorFlow machine learning platform are automatic differentiation (Autograd) and the XLA (Accelerated Linear Algebra) optimizing compiler ...

“We redefine new user level operations that are automatically executed when a TensorFlow graph is executed. That graph executes on layers of the network and we auto-insert our user operations into ...

At a technical level, TensorFlow facilitates numerical computation by using data flow graphs. According to Google (now a subsidiary of Alphabet (NASDAQ: GOOG), data flow graphs describe mathematical ...

TensorFlow uses a dataflow graph to represent computations. It shares this space with another open-source machine-learning ...