error.py 文件源码

def backward_gpu(self, inputs, grad_outputs):
        cupy = cuda.cupy
        x, t = inputs
        if hasattr(self, 'y'):
            y = self.y
        else:
            y = log_softmax._log_softmax(x)
            cupy.exp(y, out=y)
        gloss = grad_outputs[0]
        n_unit = t.size // len(t)
        if self.reduce == 'mean':
            coeff = gloss * self._coeff
        else:
            coeff = gloss[:, None, ...]

        if self.class_weight is None:
            gx = cuda.elementwise(
                'T y, S t, T coeff, S n_channel, S n_unit, S ignore_label',
                'T gx',
                '''
                    const int c = (i / n_unit % n_channel);
                    gx = t == ignore_label ? 0 : coeff * (y - (c == t));
                ''',
                'softmax_crossent_bwd')(
                    y, cupy.expand_dims(t, 1), coeff, x.shape[1],
                    n_unit, self.ignore_label)
        else:
            gx = cuda.elementwise(
                'T y, raw T w, S t, T coeff, S n_channel, S n_unit, '
                'S ignore_label',
                'T gx',
                '''
                    const int c = (i / n_unit % n_channel);
                    gx = t == ignore_label ? 0 : coeff * (y - (c == t)) * w[t];
                ''',
                'softmax_crossent_weight_bwd')(
                    y, self.class_weight, cupy.expand_dims(t, 1), coeff,
                    x.shape[1], n_unit, self.ignore_label)

        return gx, None