Methods and systems for performing inference with a neural network
OwnerMinghai QINinventor
Life of this patent
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Abstract
The present disclosure provides methods, systems, and non-transitory computer readable media for performing inference with a neural network. The systems include one or more processing units configured to instantiate a neural network comprising a bypass switch that is associated with at least two bypass networks, wherein each of the at least two bypass networks have at least one hidden layer, the bypass switch is configured to select a bypass network of the at least two bypass networks to activate, and any non-selected bypass network of the at least two bypass networks is not activated.
Claims35
An artificial neural network system, the system comprising:
- one or more processing units configured to instantiate a neural network comprising a bypass switch that is associated with at least two bypass networks, wherein each of the at least two bypass networks have at least one hidden layer, the bypass switch is configured to select a bypass network of the at least two bypass networks to activate, and any non-selected bypass network of the at least two bypass networks is not activated.
A device employing an artificial neural network, the device comprising:
- one or more processors;
- and
- a memory unit connected with the one or more processors;
- and
- a set of instructions stored on the memory unit that is executable by the one or more processors to cause the device to perform a method for performing inference with a neural network, the method comprising:
- processing an input with a neural network comprising a bypass switch that is associated with at least two bypass networks, wherein each of the at least two bypass networks have at least one hidden layer, the bypass switch selects a bypass network of the at least two bypass networks to activate, and any non-selected bypass network of the at least two bypass networks is not activated;
- and
- selecting, by the bypass switch, a bypass network of the at least two bypass networks.
A method for performing inference with a neural network, the method comprising:
- processing an input with a neural network comprising a bypass switch that is associated with at least two bypass networks, wherein each of the at least two bypass networks have at least one hidden layer, the bypass switch selects a bypass network of the at least two bypass networks to activate, and any non-selected bypass network of the at least two bypass networks is not activated;
- and
- selecting, by the bypass switch, a bypass network of the at least two bypass networks.
A non-transitory computer readable medium that stores a set of instructions that is executable by at least one processor of a computer system to cause the computer system to perform a method for performing inference with a neural network, the method comprising:
- processing an input with a neural network comprising a bypass switch that is associated with at least two bypass networks, wherein each of the at least two bypass networks have at least one hidden layer, the bypass switch selects a bypass network of the at least two bypass networks to activate, and any non-selected bypass network of the at least two bypass networks is not activated;
- and
- selecting, by the bypass switch, a bypass network of the at least two bypass networks.
A method for training a neural network, the method comprising:
- training the neural network with a training method, the neural network comprising a bypass switch that is associated with at least two bypass networks, wherein each of the at least two bypass networks have at least one hidden layer, the bypass switch selects a bypass network of the at least two bypass networks to activate, and any non-selected bypass network of the at least two bypass networks is not activated;
- and
- while the neural network is being trained with the training method, changing the bypass network selected by the bypass switch.
Dependencies are inferred from the claim text.