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 = numpy.log(x)
    if self.cache_score:
      self.y = x
    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)]
    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(()),