code: def load_meta(self, root_dir):
      meta_file = join(root_dir, "meta.yaml")
      if not exists(meta_file):
          raise ValueError(
              f"The {root_dir} should contain a `meta.yaml` file about the pointcloud sequences."
          )
  
      with open(meta_file) as f:
          self.meta = yaml.safe_load(f)
  
      self.label_to_names = self.get_label_to_names()
      self.num_classes = len(self.label_to_names)
  
      with open(meta_file) as f:
          self.meta = yaml.safe_load(f)
  
      remap_dict_val = self.meta["learning_map"]
      max_key = max(remap_dict_val.keys())
      remap_lut_val = np.zeros((max_key + 100), dtype=np.int32)
      remap_lut_val[list(remap_dict_val.keys())] = list(
          remap_dict_val.values()
      )
  
      self.remap_lut_val = remap_lut_val
  
file_path: lightning-flash/src/flash/pointcloud/segmentation/open3d_ml/sequences_dataset.py
imports: import os
  from os.path import basename, dirname, exists, isdir, isfile, join, split
  import numpy
  import yaml
  from torch.utils.data import Dataset
  from flash.core.utilities.imports import _TOPIC_POINTCLOUD_AVAILABLE
label_desc: Use image node_id 4 for calling the SequencesDataset obj's underlying member method code with example usage: obj.load_meta(root_dir) without return types