| CPC G06N 3/04 (2013.01) | 9 Claims |
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1. An inferential device, comprising:
a quantization part that quantizes a result of a convolutional operation in a first layer of a convolutional neural network using input data and weights to obtain input data for the convolutional operation in a next layer;
a convolutional operation part that includes a plurality of a shift operator and adder that is arranged for each channel that composes the input data, executes a shift operation regarding elements of the channel and weights corresponding to the elements of the channel, and adds a result of the shift operation, and an adder that adds the results of operation of the plurality of the shift operator and adder, and executes a multiplication process in the convolutional operation by the shift operation according to the value of each of elements that compose the acquired input data; and
an input data conversion part that extends a channel included in the input data to the first layer to a same number of subchannels as a number of bits of elements that compose the input data to the first layer, generates a sequence of data, provided that the value of each of the elements of a channel included in the input data to the first layer is expressed in binary numbers, by converting a value in a digit with value ‘1’ to a value that indicates a position of the value ‘1’, and by converting a value in a digit with value ‘0’ to a value that indicates a true zero, and assign each of the elements that compose the sequence of the data to each of the elements of the subchannels to enable the convolutional operation part to process both the input data to the first layer and the input data that is quantized by the quantization part in a same way.
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