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chore: update main README links to crate-specific READMEs (#1415)

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Eric Kalosa-Kenyon 2024-03-05 12:11:46 -05:00 committed by GitHub
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@ -331,7 +331,7 @@ implementation details. It is fully optimized with the
[performance characteristics mentioned earlier](#performance), as it serves as our research
playground for a variety of optimizations.
See the [WGPU Backend README](./burn-wgpu/README.md) for more details.
See the [WGPU Backend README](./crates/burn-wgpu/README.md) for more details.
</details>
@ -345,7 +345,7 @@ Based on [Candle by Hugging Face](https://github.com/huggingface/candle), a mini
for Rust with a focus on performance and ease of use, this backend can run on CPU with support for
Web Assembly or on Nvidia GPUs using CUDA.
See the [Candle Backend README](./burn-candle/README.md) for more details.
See the [Candle Backend README](./crates/burn-candle/README.md) for more details.
> _Disclaimer:_ This backend is not fully completed yet, but can work in some contexts like
> inference.
@ -362,7 +362,7 @@ PyTorch doesn't need an introduction in the realm of deep learning. This backend
[PyTorch Rust bindings](https://github.com/LaurentMazare/tch-rs), enabling you to use LibTorch C++
kernels on CPU, CUDA and Metal.
See the [LibTorch Backend README](./burn-tch/README.md) for more details.
See the [LibTorch Backend README](./crates/burn-tch/README.md) for more details.
</details>
@ -376,7 +376,7 @@ This CPU backend is admittedly not our fastest backend, but offers extreme porta
It is our only backend supporting _no_std_.
See the [NdArray Backend README](./burn-ndarray/README.md) for more details.
See the [NdArray Backend README](./crates/burn-ndarray/README.md) for more details.
</details>
@ -416,7 +416,7 @@ Of note, it is impossible to make the mistake of calling backward on a model tha
that does not support autodiff (for inference), as this method is only offered by an Autodiff
backend.
See the [Autodiff Backend README](./burn-autodiff/README.md) for more details.
See the [Autodiff Backend README](./crates/burn-autodiff/README.md) for more details.
</details>
@ -455,7 +455,7 @@ Of note, we plan to implement automatic gradient checkpointing based on compute
bound operations, which will work gracefully with the fusion backend to make your code run even
faster during training, see [this issue](https://github.com/tracel-ai/burn/issues/936).
See the [Fusion Backend README](./burn-fusion/README.md) for more details.
See the [Fusion Backend README](./crates/burn-fusion/README.md) for more details.
</details>