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Karsten Becker c21d5a3207
Add LeakyReLu implementation (#1208) 
* Implement LeakyReLu

* Cargo fmt

* Apply suggestions

* cargo fmt

* Use float_mul_scalar

* Should be grad

* Add to books module

* Move test files

* Update leaky relu to use activation function

* Update tensor.md

* Fix failing test due to approx

* Add back the function comment

* Fix comment per PR feedback

---------

Co-authored-by: Dilshod Tadjibaev <939125+antimora@users.noreply.github.com>
 		2024-03-27 13:57:51 -05:00
..
onnx-tests Add LeakyReLu implementation (#1208) 2024-03-27 13:57:51 -05:00
pytorch-tests Add Enum module support in PyTorchFileRecorder (#1436) 2024-03-11 11:21:01 -05:00
src Add LeakyReLu implementation (#1208) 2024-03-27 13:57:51 -05:00
Cargo.toml [refactor] Move burn crates to their own crates directory (#1336) 2024-02-20 13:57:55 -05:00
DEVELOPMENT.md [refactor] Move burn crates to their own crates directory (#1336) 2024-02-20 13:57:55 -05:00
LICENSE-APACHE [refactor] Move burn crates to their own crates directory (#1336) 2024-02-20 13:57:55 -05:00
LICENSE-MIT [refactor] Move burn crates to their own crates directory (#1336) 2024-02-20 13:57:55 -05:00
README.md [refactor] Move burn crates to their own crates directory (#1336) 2024-02-20 13:57:55 -05:00
SUPPORTED-ONNX-OPS.md Add LeakyReLu implementation (#1208) 2024-03-27 13:57:51 -05:00
build.rs [refactor] Move burn crates to their own crates directory (#1336) 2024-02-20 13:57:55 -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.