PyTorch bindings
OCaml bindings for PyTorch, providing NumPy-like tensor computations with GPU acceleration and automatic differentiation.
What is PyTorch bindings?
ocaml-torch is a set of OCaml bindings for PyTorch that provides tensor computations with GPU acceleration and automatic differentiation. It enables OCaml developers to perform NumPy-like operations and build neural networks using PyTorch's underlying C++ API. The project brings deep learning capabilities to the OCaml ecosystem while maintaining functional programming paradigms.
OCaml developers and researchers who want to use PyTorch's machine learning capabilities within OCaml projects, particularly those interested in functional programming approaches to deep learning.
Developers choose ocaml-torch because it provides idiomatic OCaml access to PyTorch's full feature set, including GPU acceleration and pre-trained models, without requiring Python. It enables building type-safe, functional neural networks while leveraging PyTorch's performance and ecosystem.
Overview
OCaml bindings for PyTorch
Use Cases
Best For
- Building neural networks in OCaml with GPU acceleration
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