Desparsified convolution for sparse activations
AssigneeQUALCOMM Incorporated
InventorsJamie Menjay Lin, Jian Shen, Fatih Murat Porikli
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Abstract
Certain aspects of the present disclosure provide techniques for desparsified convolution. An activation tensor is received, and a convolution output is generated for the activation tensor, comprising: selecting a subset of weight elements, corresponding to a set of non-zero elements in the activation tensor, from a weight tensor, and multiplying the set of non-zero elements and the set of weight elements.
Claims30
A processor-implemented method, comprising:
- receiving an input to a machine learning model;
- generating a first convolution output based on the input, comprising:
- generating an activation tensor based on the input;
- selecting a first subset of weight elements, corresponding to a first set of non-zero elements in the activation tensor, from a weight tensor;
- and
- multiplying the first set of non-zero elements and the first subset of weight elements;
- and
- generating an output of the machine learning model based on the first convolution output.
A system, comprising:
- memory comprising computer-executable instructions;
- and
- one or more processors configured to execute the computer-executable instructions and cause the system to perform an operation comprising:
- receiving an input to a machine learning model;
- generating a first convolution output based on the input for the activation tensor, comprising:
- generating an activation tensor based on the input;
- selecting a first subset of weight elements, corresponding to a first set of non-zero elements in the activation tensor, from a weight tensor;
- and
- multiplying the first set of non-zero elements and the first subset of weight elements;
- and
- generating an output of the machine learning model based on the first convolution output.
One or more non-transitory computer-readable media comprising instructions that, when executed by one or more processors of a processing system, cause the processing system to perform an operation comprising:
- receiving an input to a machine learning model;
- generating a first convolution output based on the input, comprising:
- generating an activation tensor based on the input;
- selecting a first subset of weight elements, corresponding to a first set of non-zero elements in the activation tensor, from a weight tensor;
- and
- multiplying the first set of non-zero elements and the first subset of weight elements;
- and
- generating an output of the machine learning model based on the first convolution output.
A system, comprising:
- means for receiving an input to a machine learning model;
- means for generating a convolution output based on the input, comprising:
- means for generating an activation tensor based on the input;
- means for selecting a subset of weight elements, corresponding to a set of non-zero elements in the activation tensor, from a weight tensor;
- and
- means for multiplying the set of non-zero elements and the subset of weight elements;
- and
- means for generating an output of the machine learning model based on the convolution output.
Dependencies are inferred from the claim text.