Expand description
nncombinator is a neural network library that allows type-safe implementation.
Modules§
- activation
- Activation Function Implementation
- arr
- Array-related data structures such as fixed-length arrays
- collection
- Definition and implementation of various collection types
- computational_
graph - Computational graph implementation
- cuda
- Function to wrap and handle cuda kernel
- device
- Computational processes used in the implementation of neural networks
- error
- Definition of various errors
- layer
- The various layers that make up a neural network and the traits they implement
- list
- Implementation of a unidirectional list to be used for memory management in a memory pool
- lossfunction
- Implementing the loss function of a neural network
- mem
- Functions related to cuda memory
- ope
- Definition and implementation of various operations on Units
- optimizer
- Definition and implementation of optimizers to be used during training
- persistence
- Implementation on persistence of neural network models
Macros§
- derive_
arithmetic - Macros for automatic derivation of the implementation of the four arithmetic operations
- derive_
arr_ like_ arithmetic - Macro for automatic derivation of the implementation of the four arithmetic operations of Arr,ArrView.ss
Structs§
Traits§
- Stack
- Trait that defines a stack to store the results computed by forward propagation when training a neural network.