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Guillaume Charifi d696d74e3d
Implement 3D and transposed 3D convolutions. (#1945) 
* Implement 3D and transposed 3D convolutions.

* Merge changes from onnx-ir #1921 pr

---------

Co-authored-by: Dilshod Tadjibaev <939125+antimora@users.noreply.github.com>
 		2024-07-02 17:54:35 -05:00
..
onnx-tests Implement 3D and transposed 3D convolutions. (#1945) 2024-07-02 17:54:35 -05:00
pytorch-tests Print module - implement module display for remaining modules (part2) (#1933) 2024-06-28 08:37:40 -04:00
src Implement 3D and transposed 3D convolutions. (#1945) 2024-07-02 17:54:35 -05:00
Cargo.toml Separating ONNX parsing from burn-import (#1921) 2024-07-02 15:17:44 -05:00
DEVELOPMENT.md [refactor] Move burn crates to their own crates directory (#1336) 2024-02-20 13:57:55 -05:00
LICENSE-APACHE Update licenses symlinks (#1613) 2024-04-12 14:43:58 -04:00
LICENSE-MIT Update licenses symlinks (#1613) 2024-04-12 14:43:58 -04:00
README.md [refactor] Move burn crates to their own crates directory (#1336) 2024-02-20 13:57:55 -05:00
SUPPORTED-ONNX-OPS.md Implement 3D and transposed 3D convolutions. (#1945) 2024-07-02 17:54:35 -05:00

README.md

Importing Models

The Burn project supports the import of models from various frameworks, emphasizing efficiency and compatibility. Currently, it handles two primary model formats:

  1. ONNX: Facilitates direct import, ensuring the model's performance and structure are maintained.

  2. PyTorch: Enables the loading of PyTorch model weights into Burn’s native model architecture, ensuring seamless integration.

Contribution

Interested in contributing to burn-import? Check out our development guide for more information.