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NMSIS-NN
Version 1.2.0
NMSIS NN Software Library
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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 |
Copy | |
Fill | |
Nndata_convert | |
SupportConversion |