INFORMATION PROCESSING SYSTEM AND INFORMATION PROCESSING METHOD
An information processing system includes a pre-processor that obtains input data; a model processor that obtains output data by inputting the input data to part of a machine learning model, and outputs the output data; and a post-processor which obtains the output data from the model processor, and executes post-processing using the output data. The model processor obtains data indicating a feature as the output data, the data being data output from the part of the machine learning model for the input data and being obtained in the middle of the prediction performed by the data. The post-processor identifies the result of the prediction performed by the machine learning model by inputting the output data to a remaining part of the machine learning model, and executes post-processing on the result of the prediction.
1 . An information processing system provided in a vehicle, the information processing system comprising:
pre-processing circuitry that obtains input data indicating a sensing result for at least one of the vehicle, surroundings of the vehicle, or an inside of the vehicle;
model processing circuitry that obtains output data by inputting the input data to at least part of a machine learning model trained to perform prediction which is predetermined, on the sensing result, and outputs the output data; and
post-processing circuitry that obtains the output data from the model processing circuitry, and executes post-processing which is predetermined, using the output data,
wherein in a first processing mode,
the model processing circuitry:
inputs the input data to the part of the machine learning model; and
obtains data indicating a feature as the output data, the data being data output from the part of the machine learning model for the input data and being obtained in a middle of the prediction performed by the machine learning model, and
the post-processing circuitry identifies a result of the prediction performed by the machine learning model by inputting the output data to a remaining part of the machine learning model, and executes the post-processing on the result of the prediction.
2 . The information processing system according to claim 1 ,
wherein in a second processing mode,
when pieces of input data each of which is the input data are obtained by the pre-processing circuitry,
the model processing circuitry:
inputs the pieces of input data to the machine learning model;
identifies results of the prediction performed by the machine learning model for the pieces of input data; and
obtains pieces of output data each of which is the output data, by executing labeling on the results of the prediction according to a predetermined rule,
in obtaining the pieces of output data,
when identical results of the prediction are identified for the pieces of input data, the model processing circuitry obtains the pieces of output data indicating different labels by executing the labeling on the identical results of the prediction, and
the post-processing circuitry identifies the identical results of the prediction by executing decoding according to the predetermined rule on the pieces of output data having different labels, and executes the post-processing on the identical results of the prediction.
3 . The information processing system according to claim 1 ,
wherein in a third processing mode,
when pieces of input data obtained by the pre-processing circuitry are sequentially input to the model processing circuitry,
the model processing circuitry:
inputs the pieces of input data to the machine learning model;
identifies results of the prediction performed by the machine learning model for the pieces of input data; and
outputs pieces of output data corresponding to the pieces of input data and indicating the results of the prediction to the post-processing circuitry in an order different from an input order of the pieces of input data input to the model processing circuitry.
4 . The information processing system according to claim 1 ,
wherein in a fourth processing mode,
when N pieces of input data are obtained by the pre-processing circuitry, and are input to the model processing circuitry, where N is an integer of 2 or greater,
the model processing circuitry:
identifies results of the prediction performed by the machine learning model for M pieces of input data among the N pieces of input data, where M is an integer of 1 or greater and N or smaller; and
obtains and outputs one piece of output data based on M results of the prediction.
5 . An information processing method to be executed by a computer provided in a vehicle, the information processing method comprising:
obtaining input data indicating a sensing result for at least one of the vehicle, surroundings of the vehicle, or an inside of the vehicle;
obtaining output data by inputting the input data to at least part of a machine learning model trained to perform prediction which is predetermined, on the sensing result, and outputting the output data;
executing post-processing which is predetermined, using the output data;
in the obtaining of the output data,
inputting the input data to the part of the machine learning model; and
obtaining data indicating a feature as the output data, the data being data output from the part of the machine learning model for the input data and being obtained in a middle of the prediction performed by the machine learning model; and
in the executing of the post-processing,
identifying the result of the prediction performed by the machine learning model by inputting the output data to a remaining part of the machine learning model, and executing the post-processing on the result of the prediction.