code: def compute_similarity_transform_batch(S1, S2):
      """Batched version of compute_similarity_transform."""
      S1_hat = np.zeros_like(S1)
      for i in range(S1.shape[0]):
          S1_hat[i] = compute_similarity_transform(S1[i], S2[i])
      return S1_hat
  
imports: import paddle
  from paddle.distributed import ParallelEnv
  import os
  import json
  from collections import defaultdict, OrderedDict
  import numpy
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 3 for calling a global function with example usage: compute_similarity_transform_batch(S1, S2) and returns: S1_hat