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#![cfg_attr(not(feature = "std"), no_std)]
#![warn(missing_docs)]

//! The core crate of Burn.

#[macro_use]
extern crate derive_new;

/// The configuration module.
pub mod config;

/// Data module.
#[cfg(feature = "std")]
pub mod data;

/// Optimizer module.
#[cfg(feature = "std")]
pub mod optim;

/// Learning rate scheduler module.
#[cfg(feature = "std")]
pub mod lr_scheduler;

/// Gradient clipping module.
pub mod grad_clipping;

/// Module for the neural network module.
pub mod module;

/// Neural network module.
pub mod nn;

/// Module for the recorder.
pub mod record;

/// Module for the tensor.
pub mod tensor;

/// Autodiff module.
#[cfg(feature = "autodiff")]
pub use burn_autodiff as autodiff;

/// Backend module.
pub mod backend;

extern crate alloc;

#[cfg(all(test, not(feature = "test-tch"), not(feature = "test-wgpu"),))]
pub type TestBackend = burn_ndarray::NdArrayBackend<f32>;

#[cfg(all(test, feature = "test-tch"))]
pub type TestBackend = burn_tch::TchBackend<f32>;

#[cfg(all(test, feature = "test-wgpu", not(target_os = "macos")))]
pub type TestBackend = burn_wgpu::WgpuBackend<burn_wgpu::Vulkan, f32, i32>;

#[cfg(all(test, feature = "test-wgpu", target_os = "macos"))]
pub type TestBackend = burn_wgpu::WgpuBackend<burn_wgpu::Metal, f32, i32>;

#[cfg(feature = "std")]
#[cfg(test)]
pub type TestADBackend = burn_autodiff::ADBackendDecorator<TestBackend>;

/// Type alias for the learning rate.
///
/// LearningRate also implements [learning rate scheduler](crate::lr_scheduler::LRScheduler) so it
/// can be used for constant learning rate.
pub type LearningRate = f64; // We could potentially change the type.