NMSIS-NN  Version 1.2.0
NMSIS NN Software Library
Here is a list of all modules:
[detail level 123]
 Convolutional Neural Network Example
 Gated Recurrent Unit Example
 PublicA collection of functions to perform basic operations for neural network layers. Functions with a _s8 suffix support TensorFlow Lite framework
 Activation FunctionsPerform activation layers, including ReLU (Rectified Linear Unit), sigmoid and tanh
 Concatenation Functions
 Convolution FunctionsCollection of convolution, depthwise convolution functions and their variants
 Fully-connected Layer FunctionsCollection of fully-connected and matrix multiplication functions
 LSTM Layer Functions
 Pooling FunctionsPerform pooling functions, including max pooling and average pooling
 Reshape Functions
 Softmax Functions
 SVDF Functions
 PrivatePerform data type conversion in-between neural network operations
 ConvolutionSupport functions for Convolution and DW Convolution
 LSTMSupport functions for LSTM
 Fully ConnectedSupport functions for Fully Connected
 SoftmaxSupport functions for Softmax
 Basic math functionsElementwise add and multiplication functions
 Basic Math Functions for Neural Network ComputationBasic Math Functions for Neural Network Computation