cross_entropy.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 = x
    gloss = grad_outputs[0]
    n_unit = t.size // len(t)
    coeff = gloss * self._coeff
    gx = cuda.elementwise(
      'T y, S t, raw T coeff, S n_channel, S n_unit',
      'T gx',
      '''
         const int c = (i / n_unit % n_channel);
         gx = (t == -1 || c != t) ? 0 : (coeff[0] * -1.0 / y);
      ''',
      'crossent_bwd')(
          y, cupy.expand_dims(t, 1), coeff, x.shape[1], n_unit)
    return gx, None