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Google’s TF-Coder tool automates machine learning model design

Researchers at Google Brain, one of Google’s AI research divisions, developed an automated tool for programming in machine learning frameworks like TensorFlow. Playing an important role are machine learning frameworks like TensorFlow, Facebook’s PyTorch, and MXNet, which enable researchers to develop and refine new models. (Tensors are algebraic objects that describe relationships between sets of things related to a vector space, and they’re a convenient data format in machine learning.) The researchers’ TF-Coder tool aims to synthesize tensor manipulation programs from input and output examples and natural language descriptions. “We believe that TF-Coder can help both machine learning beginners and experienced practitioners in writing tricky tensor transformation programs that are common in deep learning pipelines,” the coauthors wrote a preprint paper describing TF-Coder.

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