Tesseract-Torch

Tesseract-Torch is a lightweight extension to Tesseract Core that wraps Tesseracts as differentiable PyTorch operations, with full support for reverse-mode and forward-mode automatic differentiation.

The API of Tesseract-Torch consists of a single function, apply_tesseract(tesseract, inputs), which integrates any Tesseract into PyTorch’s autograd graph:

result = apply_tesseract(my_tesseract, {"x": x_tensor})
result["y"].sum().backward()  # reverse-mode AD
x_tensor.grad  # gradients flow through the Tesseract

Want to learn more? See how to get started with Tesseract-Torch, explore the API reference, or learn by example.

License

Tesseract-Torch is licensed under the Apache License 2.0 and is free to use, modify, and distribute (under the terms of the license).

Tesseract is a registered trademark of Pasteur Labs, Inc. and may not be used without permission.