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The plan for TensorFlow 2.0: delightfully productive, user-friendly workflows across a broad range of use cases, from cutting-edge research to applications development and deployment. It will no longer be a "framework", it will be an ecosystem of solutions that all work together.
In particular, it's clear to me that the same model-building API style cannot work for all users. Researchers & hackers have fundamentally different needs, constraints, and tolerance for complexity than data scientists. The key is to provide a coherent spectrum of solutions.
so we may need, and love, both Tensorflow and PyTorch ?
Is FP w/ pure functions & no OOP (or inheritance) in the roadmap? I acknowledge I may be a minority
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