leopiney/tensor-safe
A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras.
Tensor Safe is a tool for deep learning developers who need to define model architectures with guaranteed correctness. It takes your high-level model definition, written in a Haskell-like syntax, and verifies its structure at compile time. If valid, it then generates code for popular deep learning frameworks like Keras (Python) or TensorFlow.js (JavaScript).
102 stars. No commits in the last 6 months.
Use this if you are a deep learning developer or researcher working with Haskell and want to define neural network architectures with compile-time validation before deploying them to Python or JavaScript frameworks.
Not ideal if you need a library for training or running deep learning models directly in Haskell, or if you prefer to define and validate your models exclusively within existing Python or JavaScript ecosystems.
Stars
102
Forks
1
Language
Haskell
License
BSD-3-Clause
Category
Last pushed
Jan 03, 2023
Commits (30d)
0
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