PyTorch is still growing, while TensorFlow’s growth has stalled. Graph from StackOverflow trends . StackOverflow traffic for TensorFlow might not be declining at a rapid speed, but it’s ...

Google today launched an OpenCL-based mobile GPU inference engine for its TensorFlow framework on Android. It’s available now in the latest version of the TensorFlow Lite library, and the ...

TensorFlow, PyTorch, Keras, Caffe, Microsoft Cognitive Toolkit, Theano and Apache MXNet are the seven most popular frameworks for developing AI applications. Listen 0:00 . 2464 .

PyTorch, the Facebook-backed open-source library for the Python programming language, has reached version 1.9 and brings major improvements for scientific computing. PyTorch has become one of the ...

Google open-sourced the TensorFlow Runtime (TFRT), a new abstraction layer for their TensorFlow deep-learning framework that allows models to achieve better inference performance across different hard ...

PyTorch recreates the graph on the fly at each iteration step. In contrast, TensorFlow by default creates a single data flow graph, optimizes the graph code for performance, and then trains the model.

Unlike TensorFlow, PyTorch hasn’t experienced any major ruptures in the core code since the deprecation of the Variable API in version 0.4. (Previously, Variable was required to use autograd ...

In this video from the 2019 OpenFabrics Workshop in Austin, Xiaoyi Lu from Ohio State University presents: Accelerating TensorFlow with RDMA for High-Performance Deep Learning.. Google’s TensorFlow is ...

PyTorch introduced "Torchscript" and a JIT compiler, whereas TensorFlow announced that it would be moving to an "eager mode" of execution starting from version 2.0. Torchscript is essentially a ...

Developers can submit ML training jobs created in TensorFlow, Keras, PyTorch, Scikit-learn, and XGBoost. Google now offers in-built algorithms based on linear classifier, wide and deep and XGBoost ...