Expand description
§Rust LSTM Library
A complete LSTM implementation with training capabilities, multiple optimizers, and support for various architectures including peephole connections.
§Core Components
- LSTM Cells: Standard and peephole LSTM implementations with full backpropagation
- Networks: Multi-layer LSTM networks for sequence modeling
- Training: Complete training system with BPTT, gradient clipping, and validation
- Optimizers: SGD, Adam, and RMSprop optimizers with adaptive learning rates
- Loss Functions: MSE, MAE, and Cross-Entropy with numerically stable implementations
§Quick Start
use rust_lstm::models::lstm_network::LSTMNetwork;
use rust_lstm::training::create_basic_trainer;
// Create a 2-layer LSTM with 10 input features and 20 hidden units
let network = LSTMNetwork::new(10, 20, 2);
let mut trainer = create_basic_trainer(network, 0.001);
// Train on your data
// trainer.train(&train_data, Some(&validation_data));