Model ML registry and model serving
AssigneeDatabricks, Inc.
InventorsAaron Daniel Davidson, Clemens Mewald, Tomas Nykodym
Life of this patent
Estimating the term…
Abstract
A system includes an interface, a processor, and a memory. The interface is configured to receive a version of a model from a model registry. The processor is configured to store the version of the model, start a process running the version of the model, and update a proxy with version information associated with the version of the model, wherein the updated proxy indicates to redirect an indication to invoke the version of the model to the process. The memory is coupled to the processor and configured to provide the processor with instructions.
Claims20
A method comprising:
- receiving, by a model server system, an application programming interface (API) request to execute a machine learning model hosted by the model server system, the API request including execution data and a version indicator identifying a first version of the machine learning model to execute the API request, wherein the model server system hosts at least two different versions of the machine learning model and the API request was initiated by an application executing on a client device that is remote to the model server system;
- identifying the first version of the machine learning model based on the version indicator included in the API request;
- generating an input based on the execution data included in the API request;
- generating an output by providing the input to the first version of the machine learning model;
- and
- providing, to the client device, a response to the API request, the response having been generated based on the output.
A computer system comprising:
- one or more computer processors;
- and
- one or more computer-readable mediums storing instruction that, when executed by the one or more computer processors, cause the computer system to perform operations comprising:
- receiving an application programming interface (API) request to execute a machine learning model hosted by the model server system, the API request including execution data and a version indicator identifying a first version of the machine learning model to execute the API request, wherein the model server system hosts at least two different versions of the machine learning model and the API request was initiated by an application executing on a client device that is remote to the model server system;
- identifying the first version of the machine learning model based on the version indicator included in the API request;
- generating an input based on the execution data included in the API request;
- generating an output by providing the input to the first version of the machine learning model;
- and
- providing, to the client device, a response to the API request, the response having been generated based on the output.
A non-transitory computer-readable medium storing instructions that, when executed by one or more computer processors of a computer system, cause the computer system to perform operations comprising:
- receiving an application programming interface (API) request to execute a machine learning model hosted by the model server system, the API request including execution data and a version indicator identifying a first version of the machine learning model to execute the API request, wherein the model server system hosts at least two different versions of the machine learning model and the API request was initiated by an application executing on a client device that is remote to the model server system;
- identifying the first version of the machine learning model based on the version indicator included in the API request;
- generating an input based on the execution data included in the API request;
- generating an output by providing the input to the first version of the machine learning model;
- and
- providing, to the client device, a response to the API request, the response having been generated based on the output.
Dependencies are inferred from the claim text.