code: def shift_point_cloud(batch_data, shift_range=0.1):
      """Randomly shift point cloud. Shift is per point cloud.
      Input:
        BxNx3 array, original batch of point clouds
      Return:
        BxNx3 array, shifted batch of point clouds
      """
      B, N, C = batch_data.shape
      shifts = np.random.uniform(-shift_range, shift_range, (B, 3))
      for batch_index in range(B):
          batch_data[batch_index, :, :] += shifts[batch_index, :]
      return batch_data
  
imports: from lavis.common.registry import registry
  from lavis.processors.blip_processors import BlipImageBaseProcessor
  from omegaconf import OmegaConf
  import torchvision.transforms
  from lavis.models.ulip_models.utils.io import IO
  import numpy
  from PIL import Image
  import torch
label_desc: Use image node_id 9 for calling a global function with example usage: shift_point_cloud(batch_data, shift_range) and returns: batch_data