code: def compute_centered_ranks(x):
      """Return ranks that is normliazed to [-0.5, 0.5] with the rewards as input.
      Args:
          x(np.array): an array of rewards.
      """
      y = compute_ranks(x.ravel()).reshape(x.shape).astype(np.float32)
      y /= x.size - 1
      y -= 0.5
      return y
  
imports: import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: compute_centered_ranks(x) and returns: y