Patent ID: 11871043
Assignee: TENCENT AMERICA LLC
Field: Audio-visual technology (Electrical engineering)
Classification: CPC G  H | IPC G  H

Claim 7:
8. An apparatus for adaptive block partitioning for neural network model compression, the apparatus comprising:
at least one memory configured to store program code; and
at least one processor configured to read the program code and operate as instructed by the program code, the program code comprising:
reshaping code configured to cause the at least one processor to reshape a four-dimensional (4D) parameter tensor of a neural network into a 3D parameter tensor of the neural network, the 3D parameter tensor comprising a convolution kernel size, an input feature size, and an output feature size;
first partitioning code configured to cause the at least one processor to partition the 3D parameter tensor along a plane that is formed by the input feature size and the output feature size, into 3D coding tree units (CTU3Ds);
second partitioning code configured to cause the at least one processor to partition each of the CTU3Ds into a plurality of 3D coding units (CU3Ds) recursively until a maximum depth, using a quad-tree;
first constructing code configured to cause the at least one processor to construct a 3D-Unitree for each of the plurality of CU3Ds;
second constructing code configured to cause the at least one processor to construct a 3D-Tagtree for each of the plurality of CU3Ds;
first encoding code configured to cause the at least one processor to, based on a value of a parent node of the 3D-Unitree being zero, encode a corresponding unified value and skipping scanning one or more child nodes; and
second encoding code configured to cause the at least one processor to, based on the value of the parent node of the 3D-Unitree being non-zero, encode the value of the parent node of the 3D-Unitree with one of a corresponding Tagtree value or a difference in the corresponding Tagtree value between the parent node and the one or more child nodes.