Remove mention of example in backend section of the book (#2014)

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Sylvain Benner 2024-07-15 09:34:40 -04:00 committed by GitHub
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1 changed files with 5 additions and 4 deletions

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@ -8,7 +8,7 @@ entrypoint of our program, namely the `main` function defined in `src/main.rs`.
# mod data;
# mod model;
# mod training;
#
#
use crate::{model::ModelConfig, training::TrainingConfig};
use burn::{
backend::{Autodiff, Wgpu},
@ -30,9 +30,9 @@ fn main() {
}
```
In this example, we use the `Wgpu` backend which is compatible with any operating system and will
In this code snippet, we use the `Wgpu` backend which is compatible with any operating system and will
use the GPU. For other options, see the Burn README. This backend type takes the graphics API, the
float type and the int type as generic arguments that will be used during the training. The autodiff
float type and the int type as generic arguments that will be used during the training. The autodiff
backend is simply the same backend, wrapped within the `Autodiff` struct which imparts differentiability \
to any backend.
@ -47,6 +47,7 @@ You can now train your freshly created model with the command:
cargo run --release
```
When running the example, you should see the training progression through a basic CLI dashboard:
When running your project with the commande above, you should see the training progression through a
basic CLI dashboard:
<img title="a title" alt="Alt text" src="./training-output.png">