US 12,282,807 B1
Systems and methods for multi-language training of machine learning models
Xindian Long, Cary, NC (US); Liping Cai, Cary, NC (US); Xingqi Du, McKinney, TX (US); Steven Eric Krueger, Raleigh, NC (US); Joshua David Griffin, Harrisburg, NC (US); Yan Xu, Cary, NC (US); Scott Russell Pope, Cary, NC (US); and Lawrence Edmund Lewis, Durham, NC (US)
Assigned to SAS INSTITUTE INC., Cary, NC (US)
Filed by SAS Institute Inc., Cary, NC (US)
Filed on Dec. 23, 2024, as Appl. No. 19/000,691.
Application 19/000,691 is a continuation in part of application No. 19/000,641, filed on Dec. 23, 2024.
Claims priority of provisional application 63/680,807, filed on Aug. 8, 2024.
Claims priority of provisional application 63/660,761, filed on Jun. 17, 2024.
Claims priority of provisional application 63/637,188, filed on Apr. 22, 2024.
Int. Cl. G06F 9/54 (2006.01); G06N 20/00 (2019.01)
CPC G06F 9/54 (2013.01) [G06N 20/00 (2019.01)] 30 Claims
OG exemplary drawing
 
1. A computer-program product comprising a non-transitory machine-readable storage medium storing computer instructions that, when executed by one or more processors, perform operations comprising:
receiving, by a controller node, a request to execute a client process associated with a first programming language and a plurality of threads;
launching, by the controller node, a plurality of multi-language worker processes based on a number of threads associated with the client process;
executing the plurality of threads associated with the client process using the plurality of multi-language worker processes, wherein executing a respective thread of the client process at a respective multi-language worker process includes:
loading a machine learning library associated with a second programming language;
executing, by the machine learning library, a multi-threaded data processing extension that receives one or more data messages, formatted in the first programming language, from the respective thread of the client process;
generating, by the multi-threaded data processing extension, one or more training artifacts based on the one or more data messages formatted in the first programming language;
training, by the machine learning library, a machine learning model in the second programming language based on the one or more training artifacts; and
transmitting, to the controller node, by the multi-threaded data processing extension, one or more second data messages that are formatted in the first programming language and include feedback data associated with the training of the machine learning model.