Expand description
Ergonomics & safety focused deep learning in Rust. Main features include:
- Tensor library, complete with const generic shapes, activation functions, and more.
- Safe & Easy to use neural network building blocks.
- Standard deep learning optimizers such as Sgd and Adam.
- Reverse mode auto differentiation[1] implementation.
Modules
Provides implementations for modifying Nd arrays on the CPU.
Standard loss functions such as mse, mae, cross entropy, and more.
Provides some generic functions to save Nd arrays in the .npy format.
Implementations of all operations for tensors, including activations, binary operations, and other methods.