Methods and systems for generating the gradients of a loss function with respect to the weights of a convolution layer

Abstract

Methods and systems of generating gradients of a loss metric for a neural network (NN) with respect to weights of a convolution layer of the NN, the convolution layer of the NN configured to receive an input tensor of input values and a weight tensor of weights, and generate an output tensor of output values. The methods comprise performing, using hardware logic, a group convolution between a first y-dimensional tensor and a second z-dimensional tensor wherein z=y+1, the first y-dimensional tensor being formed of a set of values from the input tensor, and the second z-dimensional tensor being formed of a set of values from an output gradient tensor comprising gradients of the loss metric for the NN with respect to the output values; wherein the first y-dimensional tensor, the second z-dimensional tensor and the group convolutions are configured to generate an output of a convolution operation between each channel of the set of values of the input tensor and each channel of the set of values of the output gradient tensor.