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
Activation Functions	Perform activation layers, including ReLU (Rectified Linear Unit), sigmoid and tanh
GroupElementwise
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
▼Pooling Functions	Perform pooling functions, including max pooling and average pooling
GetBufferSizePooling
Reshape Functions
Softmax Functions
SVDF Functions
▼Private	Perform data type conversion in-between neural network operations
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
Basic math functions	Elementwise add and multiplication functions
Basic Math Functions for Neural Network Computation	Basic Math Functions for Neural Network Computation
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Nndata_convert
SupportConversion