def updateOutput(self, input, y):
self.buffer = self.buffer or input.new()
self.buffer.resize_as_(input).copy_(input)
self.buffer[torch.eq(y, -1.)] = 0
self.output = self.buffer.sum()
self.buffer.fill_(self.margin).add_(-1, input)
self.buffer.cmax_(0)
self.buffer[torch.eq(y, 1.)] = 0
self.output = self.output + self.buffer.sum()
if self.sizeAverage:
self.output = self.output / input.nelement()
return self.output
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