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Many programming languages which were not designed with differentiable programming in mind can gain differentiability features by calling on a differentiable programming framework via an [[Application programming interface|API]]. For example, [[TensorFlow]] can be called from [[Python (programming language)|Python]], [[JavaScript]], [[C++]], [[Java (programming language)|Java]], [[Go (programming language)|Go]], and [[Swift (programming language)|Swift]].<ref>{{Cite web|url=https://www.tensorflow.org/api_docs|title=API Documentation {{!}} TensorFlow Core r1.14|website=TensorFlow|language=en|access-date=2019-06-20}}</ref>
Differentiable programming in Swift with TensorFlow extends the type system to make differentiable functions first-class values, and is implemented as a compiler transformation on the Swift intermediate language ([https://github.com/apple/swift/blob/tensorflow/docs/SIL.rst SIL]). It leverages [[Protocol (object-oriented programming)|protocol-oriented programming]] ([[Type class|type classes]]) to allow custom differentiable data structures. The authors hope that it will become a fully integrated part of the Swift language in the future.<ref>{{Cite web|url=https://forums.swift.org/t/pre-pre-pitch-swift-differentiable-programming-design-overview/25992|title=Pre-pre-pitch: Swift Differentiable Programming Design Overview|date=2019-06-17|website=Swift Forums|language=en-US|access-date=2019-06-18}}</ref>
==See also==
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