VAE_util.py 文件源码

def tf_2d_normal(x1, x2, mu1, mu2, s1, s2, rho):
  """ 2D normal distribution
  input
  - x,mu: input vectors
  - s1,s2: standard deviances over x1 and x2
  - rho: correlation coefficient in x1-x2 plane
  """
  # eq # 24 and 25 of http://arxiv.org/abs/1308.0850
  norm1 = tf.sub(x1, mu1)
  norm2 = tf.sub(x2, mu2)
  s1s2 = tf.mul(s1, s2)
  z = tf.square(tf.div(norm1, s1))+tf.square(tf.div(norm2, s2))-2.0*tf.div(tf.mul(rho, tf.mul(norm1, norm2)), s1s2)
  negRho = 1-tf.square(rho)
  result = tf.exp(tf.div(-1.0*z,2.0*negRho))
  denom = 2*np.pi*tf.mul(s1s2, tf.sqrt(negRho))
  px1x2 = tf.div(result, denom)
  return px1x2