US 12,189,599 B2
Lookup table activation functions for neural networks
Albert Antony, San Jose, CA (US); Francesco Rossi, Sunnyvale, CA (US); Guillaume Tartavel, Cupertino, CA (US); Xiaojin Shi, Cupertino, CA (US); and Marco Zuliani, San Jose, CA (US)
Assigned to Apple Inc., Cupertino, CA (US)
Filed by Apple Inc., Cupertino, CA (US)
Filed on Sep. 22, 2020, as Appl. No. 17/028,920.
Claims priority of provisional application 63/041,781, filed on Jun. 19, 2020.
Prior Publication US 2021/0397596 A1, Dec. 23, 2021
Int. Cl. G06F 16/22 (2019.01); G06N 3/04 (2023.01)
CPC G06F 16/2282 (2019.01) [G06N 3/04 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of computing an output of a neural network, comprising:
obtaining an input value for an activation function associated with a node of the neural network;
obtaining, based on the input value, a lookup table value corresponding to each of a plurality of lookup tables that correspond to the activation function associated with the node of the neural network; and
determining a value of the activation function for the input value by combining the obtained lookup table values corresponding to the plurality of lookup tables.