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.

Google open-sourced TFRT, a faster and more efficient runtime that'll eventually replace the default runtime in the company's TensorFlow framework.

TensorFlow 2.0, released in 2019, introduced improved usability, eager execution, and tighter integration with Keras, making it more accessible for AI researchers and developers.

Both PyTorch and TensorFlow have quite developed ecosystems, including repositories for trained models other than HuggingFace, data management systems, failure prevention mechanisms, and more.

The deep learning framework PyTorch has infiltrated the enterprise thanks to its relative ease of use. Three companies tell us why they chose PyTorch over Google’s renowned TensorFlow framework.

Is PyTorch better than TensorFlow for general use cases? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world ...

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-Transformers is currently used for NLP tasks by more than 1,000 companies, including Microsoft’s Bing, Apple, and Stitch Fix. Use this web app to try out the Hugging Face Transformers ...