code: def _loaders(self):
      loaders = []
      if self.has_train_loader:
          loaders += [self.train_dataloader]
      if self.has_val_loader:
          loaders += [self.val_dataloader]
      if self.has_test_loaders:
          loaders += self.test_dataloaders
      return loaders
  
imports: import os
  from abc import ABC, abstractmethod
  import logging
  import functools
  from functools import partial
  import numpy
  import torch
  import torch_geometric
  from torch_geometric.transforms import Compose, FixedPoints
  import copy
  from torch_points3d.models import model_interface
  from torch_points3d.core.data_transform import instantiate_transforms, MultiScaleTransform
  from torch_points3d.core.data_transform import instantiate_filters
  from torch_points3d.datasets.batch import SimpleBatch
  from torch_points3d.datasets.multiscale_data import MultiScaleBatch
  from torch_points3d.utils.enums import ConvolutionFormat
  from torch_points3d.utils.config import ConvolutionFormatFactory
  from torch_points3d.utils.colors import COLORS, colored_print
label_desc: Use image node_id 23 for calling the BaseDataset obj's underlying member method code with example usage: obj._loaders() and returns: loaders