Documentation
Everything you need to build, train, and deploy deep learning models with RUMUS. From first principles to production-ready GPU-accelerated pipelines — all with the safety and performance guarantees of Rust.
Getting Started
Install RUMUS, build your first neural network, and train it in minutes. A hands-on introduction to the framework.
Read moreTensors
Learn how RUMUS tensors work — creation, indexing, broadcasting, and efficient memory layout backed by Rust's ownership model.
Read moreAutograd
Understand automatic differentiation in RUMUS. Build computation graphs, call backward(), and inspect gradients with zero-cost abstractions.
Read moreNeural Networks
Compose models with Linear, Conv2d, MaxPool2d, Flatten, and Dropout layers. Use the #[derive(Module)] proc macro for ergonomic model definitions.
Read moreOptimizers
Train your models with SGD, Adam, and AdamW optimizers. Configure learning rates, momentum, weight decay, and scheduler strategies.
Read moreGPU Acceleration
Accelerate training and inference with WGPU. Move tensors to the GPU, run cross-platform compute shaders, and benchmark performance.
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