a33253b2e850ded23f4661555d65bd01082ecb55,chainer/functions/math/average.py,Sum,forward,#Sum#Any#,52

Before Change

        x, = inputs
        ret = x.sum(axis=self.axis, keepdims=self.keepdims)
        if backend.get_array_module(x) is numpy:
            ret = numpy.asarray(ret)
        return ret,

    def backward(self, indexes, grad_outputs):
        gy, = grad_outputs

After Change

    def forward(self, inputs):
        x, = inputs
        if self.axis is None:
            self.multiplier = 1.0 / x.size
        else:
            divider = 1
            for axis in self.axis:
                divider *= x.shape[axis]
            self.multiplier = 1.0 / divider
        ret = utils.force_array(
            x.mean(axis=self.axis, keepdims=self.keepdims))
        return ret,

Instances