softmax_cross_entropy.py 文件源码

def forward_cpu(self, inputs):
        x, t = inputs
        if chainer.is_debug():
            self._check_input_values(x, t)

        log_y = softmax_log(x, False)
        if self.cache_score:
            self.y = numpy.exp(log_y)
        log_yd = numpy.rollaxis(log_y, 1)
        log_yd = log_yd.reshape(len(log_yd), -1)

        log_p = log_yd[numpy.maximum(t.ravel(), 0), six.moves.range(t.size)]
        # deal with the case where the SoftmaxCrossEntropy is
        # unpickled from the old version
        if getattr(self, 'normalize', True):
            count = (t != self.ignore_label).sum()
        else:
            count = len(x)
        self._coeff = 1.0 / max(count, 1)

        y = (log_p * (t.ravel() != self.ignore_label)).sum(keepdims=True) \
            * (-self._coeff)
        return y.reshape(()),