Modules

Here is a list of all modules:

[detail level 123]

Convolutional Neural Network Example
Gated Recurrent Unit Example
▼Public	A collection of functions to perform basic operations for neural network layers. Functions with a _s8 suffix support TensorFlow Lite framework
Structure Types	Enums and Data Structures used in public API
Activation Functions	Perform activation layers, including ReLU (Rectified Linear Unit), sigmoid and tanh
Elementwise Functions	Elementwise add and multiplication functions
Concatenation Functions
▼Convolution Functions	Collection of convolution, depthwise convolution functions and their variants
GetBufferSizeNNConv
▼Fully-connected Layer Functions	Collection of fully-connected and matrix multiplication functions
GetBufferSizeFC
LSTM Layer Functions	Get size of additional buffer required by riscv_svdf_s8() for Arm(R) Helium Architecture case. Refer to riscv_svdf_s8_get_buffer_size() for function argument details
▼Pooling Functions	Perform pooling functions, including max pooling and average pooling
GetBufferSizePooling
Reshape Functions
Softmax Functions
▼SVDF Functions
GetBufferSizeSVDF
▼Private	Internal Support functions. Not intended to be called direclty by a NMSIS-NN user
Structure Types	Data structure types used by private functions
Convolution	Support functions for Convolution and DW Convolution
LSTM	Support functions for LSTM
Fully Connected	Support functions for Fully Connected
Softmax	Support functions for Softmax
BasicMath
Basic Math Functions for Neural Network Computation	Basic Math Functions for Neural Network Computation
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Fill
Nndata_convert
Data Conversion	Perform data type conversion in-between neural network operations