US 12,411,709 B2
Annotation of a machine learning pipeline with operational semantics
Raghu Kiran Ganti, White Plains, NY (US); Mudhakar Srivatsa, White Plains, NY (US); and Carlos Henrique Andrade Costa, White Plains, NY (US)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Nov. 30, 2021, as Appl. No. 17/538,301.
Prior Publication US 2023/0168923 A1, Jun. 1, 2023
Int. Cl. G06F 9/46 (2006.01); G06F 9/48 (2006.01)
CPC G06F 9/4881 (2013.01) 20 Claims
OG exemplary drawing
 
1. A computer system comprising:
a processor operatively coupled to memory;
an artificial intelligence (AI) platform, operatively coupled to the processor, comprising:
a pipeline manager configured to represent a pipeline in a data flow graph (DFG) with individual nodes representing an instance of a mathematical operation and individual edges representing an object;
a processing manager configured to pre-processing the pipeline represented in the DFG, including selectively annotate one or more of the nodes in the DFG with two or more operational semantics, the semantics comprising an input combination, a firing combination, a state of the node, an output condition, or a combination thereof; and
an evaluator configured to evaluate the annotated DFG and control a scheduling order responsive to the evaluation, including discover an order of execution based on the node annotations; and
a director configured to execute the pipeline represented in the annotated DFG responsive to the evaluation, and construct output from the executed pipeline, the constructed output configured to align with an output condition semantic.