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TF-Coder: Program Synthesis for Tensor Manipulations
2022
ACM Transactions on Programming Languages and Systems
The success and popularity of deep learning is on the rise, partially due to powerful deep learning frameworks such as TensorFlow and PyTorch that make it easier to develop deep learning models. However, these libraries also come with steep learning curves, since programming in these frameworks is quite different from traditional imperative programming with explicit loops and conditionals. In this work, we present a tool called TF-Coder for programming by example in TensorFlow. TF-Coder uses a
doi:10.1145/3517034
fatcat:dqqhqvtevnefdgn7zihokv636u