whitening_util.py 文件源码

def regularized_inverse2(svd, L=1e-3):
  """Regularized inverse, working from SVD"""
  if svd.__class__.__name__=='SvdTuple' or svd.__class__.__name__=='SvdWrapper':
    (s, u, v) = (svd.s, svd.u, svd.v)
  else:
    assert False, "Unknown type"
  max_eigen = tf.reduce_max(s)
  #  max_eigen = tf.Print(max_eigen, [max_eigen], "max_eigen")
  #si = 1/(s + L*tf.ones_like(s)/max_eigen)
  si = 1/(s+L*tf.ones_like(s))
  return u @ tf.diag(si) @ tf.transpose(v)