Improper neural network input detection and handling
AssigneeAmazon Technologies, Inc.
InventorsRandy Renfu Huang, Richard John Heaton, Andrea Olgiati, Ron Diamant
Life of this patent
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Abstract
Systems and methods for performing improper input data detection are described. In one example, a system comprises: hardware circuits configured to receive input data and to perform computations of a neural network based on the input data to generate computation outputs; and an improper input detection circuit configured to: determine a relationship between the computation outputs of the hardware circuits and reference outputs; determine that the input data are improper based on the relationship; and perform an action based on determining that the input data are improper.
Claims19
A method comprising:
- performing computations based on input data received from an application to generate intermediate outputs of a neural network layer;
- generating outputs of the neural network layer based on applying activation function processing on the intermediate outputs;
- receiving a mean and a standard deviation of reference outputs of the neural network layer;
- for each of the outputs of the neural network layer:
- determining a difference between the each output and the mean;
- comparing the difference against one or more thresholds, the one or more thresholds determined based on a pre-determined multiplier of the standard deviations;
- and
- determining, based on a result of the comparison, whether the each output is an outlier output;
- determining a total count of the outlier outputs;
- determining that the input data are improper based on a comparison between the total count and a second threshold;
- and
- based on determining that the input data are improper, performing at least one of:
- transmitting a notification to the application, or suspending computations of a subsequent neural network layer at arithmetic circuits.
A system comprising:
- hardware circuits configured to receive input data and to perform computations of a neural network based on the input data to generate computation outputs, the neural network having been trained using a set of training data, wherein the hardware circuits comprise:
- activation function circuits configured to apply activation function processing to generate the computation outputs;
- and
- an improper input detection circuit configured to:
- determine a relationship between the computation outputs generated by the activation function circuits and reference outputs, wherein the reference outputs are generated based on processing the set of training data using the neural network;
- determine that the input data are improper based on the relationship;
- and
- perform an action based on determining that the input data are improper.
A method, comprising:
- receiving, from hardware circuits, computation outputs of a neural network based on input data provided by an application, the neural network having been trained using a set of training data, wherein the hardware circuits comprise activation function circuits that apply activation function processing to generate the computation outputs;
- determining a relationship between the computation outputs generated by the activation function circuits and reference outputs, wherein the reference outputs are generated based on processing the set of training data using the neural network;
- determining that the input data are improper based on the relationship;
- and
- performing an action based on determining that input data are improper.
Dependencies are inferred from the claim text.