Data feature extraction method and related apparatus

A processor of a data feature extraction apparatus, the processor comprising:

• an operation circuit, wherein the operation circuit includes a first subcircuit and a second subcircuit, the first subcircuit includes M*N operation components, and M and N are positive integers;
• wherein the operation circuit is configured to determine second feature extraction parameters based on first feature extraction parameters, which are read by a reader of the data feature extraction apparatus from a target memory;
• wherein the second feature extraction parameters comprise M*N parameters;
• wherein the operation circuit is further configured to determine second to-be-extracted feature data based on first to-be-extracted feature data, which is read by the reader from the target memory;
• wherein the second to-be-extracted feature data comprises M*N pieces of data, and the M*N pieces of data are in a one-to-one correspondence with the M*N parameters wherein the M*N operation components are separately in a one-to-one correspondence with the M*N parameters and the M*N pieces of data;
• each of the M*N operation components is configured to compute an absolute value of a difference between a target parameter input into each operation component and target data input into each operation;
• and
• the second subcircuit is configured to compute and output a sum of absolute values output by all the M*N operation components;
• wherein the sum is used to obtain feature data of a target feature in the second to-be-extracted feature data.

A data feature extraction apparatus comprising:

• a reader, configured to read first feature extraction parameters from a target memory, wherein the first feature extraction parameters comprise parameters obtained by performing first quantization processing on network parameters, wherein the network parameters are in a target neural network and that are used to extract a target feature;
• a processor, configured to determine second feature extraction parameters based on the first feature extraction parameters, wherein the second feature extraction parameters comprise M*N parameters, and M and N are positive integers, wherein
• the reader is further configured to read first to-be-extracted feature data from the target memory, and the first to-be-extracted feature data is data obtained by performing second quantization processing on initial to-be-extracted feature data, and
• the processor is further configured to determine second to-be-extracted feature data based on the first to-be-extracted feature data, wherein the second to-be-extracted feature data comprises M*N pieces of data, and the M*N pieces of data are in a one-to-one correspondence with the M*N parameters;
• and
• a feature extractor, configured to perform an addition convolution operation on the second feature extraction parameters and the second to-be-extracted feature data by using a target processor, to obtain first feature data, wherein the addition convolution operation comprises:
• computing an absolute value of a difference between each of the M*N parameters and corresponding data to obtain M*N absolute values;
• and computing a sum of the M*N absolute values.