Friday, March 30, 2018

Swift for TensorFlow


Swift for TensorFlow is a result of first-principles thinking applied to machine learning frameworks, and works quite differently than existing TensorFlow language bindings. Whereas prior solutions are designed within the constraints of what can be achieved by a (typically Python or Lua) library, Swift for TensorFlow is based on the belief that machine learning is important enough to deserve first-class language and compiler support.

First-class language and compiler support allows us to innovate in areas that have traditionally been out of bounds for machine learning libraries. Our results provide the performance of TensorFlow graphs with the ease of use of define-by-run models, and provides a great user experience - for example, by catching more mistakes before you run your code.

Chris Lattner:

This is an early stage project which isn’t ready for use by general machine learning researchers. We are open sourcing the project early while it is still possible to change anything about its design, allowing the project to benefit from the expertise of the broader community. We don’t have 1.0 release plans, but will discuss that when it comes closer.

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