mirror of https://github.com/tracel-ai/burn.git
Fix guide project name in the book (#1631)
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@ -28,9 +28,7 @@ fn main() {
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You might be wondering why we use the `guide` prefix to bring the different modules we just
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implemented into scope. Instead of including the code in the current guide in a single file, we
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separated it into different files which group related code into _modules_. The `guide` is simply the
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name we gave to our _crate_, which contains the different files. If you named your project crate
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as `my-first-burn-model`,
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you can equivalently replace all usages of `guide` above with `my-first-burn-model`. Below is a brief explanation of the
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name we gave to our _crate_, which contains the different files. Below is a brief explanation of the
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different parts of the Rust module system.
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A **package** is a bundle of one or more crates that provides a set of functionality. A package
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@ -40,9 +38,9 @@ A **crate** is a compilation unit in Rust. It could be a single file, but it is
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split up crates into multiple _modules_ and possibly multiple files. A crate can come in one of two
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forms: a binary crate or a library crate. When compiling a crate, the compiler first looks in the
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crate root file (usually `src/lib.rs` for a library crate or `src/main.rs` for a binary crate). Any
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module declared in the crate root file will be inserted in the crate for compilation. For this demo example, we will
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define a library crate where all the individual modules (model, data, training, etc.) are listed inside `src/lib.rs` as
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follows:
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module declared in the crate root file will be inserted in the crate for compilation. For this demo
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example, we will define a library crate where all the individual modules (model, data, training,
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etc.) are listed inside `src/lib.rs` as follows:
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```
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pub mod data;
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@ -52,11 +50,11 @@ pub mod training;
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```
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A **module** lets us organize code within a crate for readability and easy reuse. Modules also allow
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us to control the _privacy_ of items. The `pub` keyword used above, for example, is employed to make a module publicly
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available inside the crate.
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us to control the _privacy_ of items. The `pub` keyword used above, for example, is employed to make
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a module publicly available inside the crate.
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The entry point of our program is the `main` function, defined in the `examples/guide.rs` file. The file structure
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for this example is illustrated below:
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The entry point of our program is the `main` function, defined in the `examples/guide.rs` file. The
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file structure for this example is illustrated below:
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```
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guide
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@ -72,8 +70,8 @@ guide
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```
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The source for this guide can be found in our
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[GitHub repository](https://github.com/tracel-ai/burn/tree/main/examples/guide) which can be used to run this basic
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workflow example end-to-end.\
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[GitHub repository](https://github.com/tracel-ai/burn/tree/main/examples/guide) which can be used to
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run this basic workflow example end-to-end.\
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</details><br>
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@ -4,17 +4,17 @@ The first step is to create a project and add the different Burn dependencies. S
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new project with Cargo:
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```console
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cargo new my-first-burn-model
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cargo new guide
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```
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As [mentioned previously](../getting-started.md#creating-a-burn-application), this will initialize
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your `my-first-burn-model` project directory with a `Cargo.toml` and a `src/main.rs` file.
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your `guide` project directory with a `Cargo.toml` and a `src/main.rs` file.
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In the `Cargo.toml` file, add the `burn` dependency with `train`, `wgpu` and `vision` features.
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```toml
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[package]
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name = "my-first-burn-model"
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name = "guide"
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version = "0.1.0"
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edition = "2021"
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@ -279,9 +279,10 @@ network modules already built with Burn use the `forward` nomenclature, simply b
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standard in the field.
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Similar to neural network modules, the [`Tensor`](../building-blocks/tensor.md) struct given as a
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parameter also takes the Backend trait as a generic argument, alongside its dimensionality. Even if it is not
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used in this specific example, it is possible to add the kind of the tensor as a third generic
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argument. For example, a 3-dimensional Tensor of different data types(float, int, bool) would be defined as following:
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parameter also takes the Backend trait as a generic argument, alongside its dimensionality. Even if
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it is not used in this specific example, it is possible to add the kind of the tensor as a third
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generic argument. For example, a 3-dimensional Tensor of different data types(float, int, bool)
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would be defined as following:
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```rust , ignore
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Tensor<B, 3> // Float tensor (default)
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