rumus 0.1.2

A native-Rust deep learning framework with explicit memory safety and hardware acceleration
Documentation 
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//! Neural network building blocks: parameters, modules, layers, losses, and IO.

mod activations;
mod conv;
mod dropout;
mod flatten;
mod io;
mod linear;
mod loss;
mod module;
mod parameter;
mod pool;

pub use activations::relu;
pub use conv::Conv2d;
pub use dropout::Dropout;
pub use flatten::Flatten;
pub use io::{load_safetensors, save_safetensors};
pub use linear::Linear;
pub use loss::{cross_entropy_loss, mse_loss};
pub use pool::MaxPool2d;
pub use module::Module;
#[cfg(feature = "gpu")]
pub use module::ModuleToGpu;
pub use parameter::Parameter;

// Re-export the derive macro so users can write `use rumus::nn::Module;`
// and `#[derive(Module)]` in the same scope.
pub use rumus_macros::Module;