Managing a Machine Learning Environment
AssigneeAptiv Technologies AG
InventorsMiguel A. Aguilar, Paul Dragan, Christian Prediger
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Abstract
A method and computing device are disclosed herein for managing a machine learning (ML) environment, the method comprising receiving, by a ML controller, ML model information from a ML application, the ML model information comprising a ML model definition and ML model metadata comprising information specifying a ML runtime to execute a ML model; and generating, by the ML controller, a model runner instance in an abstraction layer at the ML controller using the received ML model information, the model runner instance being configured to interact with the specified ML runtime hosted by a target ML platform to cause the ML runtime to execute the ML model.
Claims20
A method the method comprising:
- managing, by a machine learning (ML) controller, a ML environment by:
- receiving, by the ML controller, ML model information from a ML application, the ML model information comprising a ML model definition and ML model metadata comprising information specifying a ML runtime to execute a ML model;
- and
- generating, by the ML controller, a model runner instance in an abstraction layer at the ML controller using the received ML model information, the model runner instance being configured to interact with the specified ML runtime hosted by a target ML platform to cause the ML runtime to execute the ML model.
A computer-readable medium comprising instructions that, when executed by a computer, cause the computer to manage a machine learning (ML) environment by causing a ML controller to:
- receive ML model information from a ML application, the ML model information comprising a ML model definition and ML model metadata comprising information specifying a ML runtime to execute a ML model;
- and
- generate a model runner instance in an abstraction layer at the ML controller using the received ML model information, the model runner instance being configured to interact with the specified ML runtime hosted by a target ML platform to cause the ML runtime to execute the ML model.
A computing device, the computing device comprising:
- a memory storing computer-readable instructions for a machine learning (ML) controller to manage a ML environment;
- and
- a ML controller configured to execute the instruction to cause the ML controller to:
- receive, from a ML application, ML model information, the ML model information comprising a ML model definition and ML model metadata comprising information specifying a ML runtime to execute a ML model;
- and
- generate, with a model runner instance generator configured to generate a model runner instance in an abstraction layer at the ML controller using the received ML model information, the model runner instance being configured to interact with the specified ML runtime hosted by a target ML platform to cause the ML runtime to execute the ML model.
Dependencies are inferred from the claim text.