Overview
Tensor2Tensor (T2T) is a deep learning library developed by Google Brain. It focuses on sequence-to-sequence models, aiming to simplify research and development in areas like translation, summarization, and image captioning. T2T supports various datasets and model architectures, including transformers, LSTMs, and convolutional networks. It utilizes a problem-centric approach, where data is preprocessed into a common format that can be used across different models. The library is designed to be modular and extensible, allowing researchers to easily add new datasets, models, and training techniques. While deprecated in favor of Trax, T2T remains useful for legacy projects and educational purposes, offering a range of pre-trained models and example scripts for tasks such as image classification, language modeling, and sentiment analysis.