rustyml 0.16.0

A high-performance machine learning & deep learning library in pure Rust, offering ML algorithms and neural network support
Documentation 
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//! Regularization layers
//!
//! Re-exports the 3 families of regularization layers, plus a private `validation` submodule
//! of parameter and input-shape checks shared across the layers.
//!
//! The families are:
//! - dropout: [`Dropout`](crate::neural_network::layers::Dropout) and the spatial variants
//!   [`SpatialDropout1D`](crate::neural_network::layers::SpatialDropout1D),
//!   [`SpatialDropout2D`](crate::neural_network::layers::SpatialDropout2D), and
//!   [`SpatialDropout3D`](crate::neural_network::layers::SpatialDropout3D)
//! - noise injection: [`GaussianNoise`](crate::neural_network::layers::GaussianNoise) and
//!   [`GaussianDropout`](crate::neural_network::layers::GaussianDropout)
//! - normalization: [`BatchNormalization`](crate::neural_network::layers::BatchNormalization),
//!   [`LayerNormalization`](crate::neural_network::layers::LayerNormalization),
//!   [`GroupNormalization`](crate::neural_network::layers::GroupNormalization),
//!   [`InstanceNormalization`](crate::neural_network::layers::InstanceNormalization), and
//!   [`UnitNormalization`](crate::neural_network::layers::UnitNormalization)
//!
//! Every dropout layer, every noise layer, and `BatchNormalization` change what forward computes
//! between training and inference. `LayerNormalization`, `GroupNormalization`,
//! `InstanceNormalization`, and `UnitNormalization` give the same output either way. Each one
//! takes its statistic from a single sample, never from the batch. The mode is not a field of a
//! layer. It is the training flag of the [`Ctx`](crate::neural_network::Ctx) that the pass
//! carries, and every layer of this module reads it with
//! [`Ctx::is_training`](crate::neural_network::Ctx::is_training)

/// Dropout layers for neural networks
pub mod dropout;
/// Noise injection layers for neural networks
pub mod noise_injection;
/// Normalization layers for neural networks
pub mod normalization;
/// Input validation functions for regularization layers
mod validation;

pub use dropout::*;
pub use noise_injection::*;
pub use normalization::*;