1.5. The Prelude and Imports

1.5.1. Three ways to bring names into scope

Glob the whole prelude

use rustyml::prelude::*;

This pulls everything into the current scope. It suits getting code written quickly, without having to look up where each item lives.

Glob a single prelude category

The prelude is split into four submodules, so you can import just what you need:

use rustyml::prelude::machine_learning::*; // classical estimators, traits, and shared enums
use rustyml::prelude::neural_network::*;   // Sequential, History, Tensor, layers, losses, optimizers
use rustyml::prelude::metrics::*;          // the evaluation-metric functions and types
use rustyml::prelude::utils::*;            // standardize, normalize, scalers, encoders, split

Use this when the file you are writing clearly belongs to a single domain.

Import by exact path

use rustyml::machine_learning::LinearRegression;
use rustyml::traits::{Fit, Predict};
use rustyml::metrics::r2_score;

Library code that has to be maintained long-term should prefer this style.

1.5.2. What the prelude re-exports

The prelude is a hand-picked list: it re-exports only the items you reach for often. The tables below show exactly what each prelude submodule re-exports.

Machine learning

Neural network

Note the exact casing on RMSprop (lowercase p). Activations come in two forms: one is the standalone layers ReLU/Softmax/Linear/Sigmoid/Tanh. The other is, in any layer that accepts an Activation enum, either picking a variant (Activation::ReLU, Activation::Softmax, Activation::Linear, Activation::Sigmoid, Activation::Tanh) or passing one of those standalone activation layers instead (they impl Layer and convert Into<Activation>).

For example, one of Dense::new’s parameters is activation: impl Into<Activation>, so you can pass either an Activation enum variant or a standalone activation layer: Dense::new(3, 8, Activation::ReLU) and Dense::new(3, 8, ReLU::new()) are equivalent.

Metrics

Unlike the error-propagation design in the rest of the crate, the metric functions panic outright on an error, which keeps the module lightweight; see 5. Model Evaluation. Their argument order is (y_true, y_pred), matching scikit-learn.

Utilities

1.5.3. Feature gates decide what the prelude contains

The rustyml::prelude module is always compiled, but each submodule only appears once the matching module feature is enabled. So use rustyml::prelude::* does not mean everything RustyML can do — it means everything the features you enabled can do. For what each feature contains, see 1.2 Installation and Feature Flags.

1.5.4. Using fully-qualified paths

To find where an item lives, docs.rs/rustyml is the place to look. Here is a lookup table for the main types: