model.py 文件源码

def inv_model_spec(y):
  # construct inverse pass for sampling
  shape = final_latent_dimension
  z = tf.reshape(y, [-1, shape[1], shape[2], shape[3]])
  y = None
  for layer in reversed(layers):
    y,z = layer.backward(y,z)

  # inverse logit
  x = tf.inv(1 + tf.exp(-y))

  return x