code: def __repr__(self):
      message = "Dataset: %s \n" % self.__class__.__name__
      for attr in self.__dict__:
          if "transform" in attr:
              message += "{}{} {}= {}\n".format(
                  COLORS.IPurple,
                  attr,
                  COLORS.END_NO_TOKEN,
                  getattr(self, attr),
              )
      for attr in self.__dict__:
          if attr.endswith("_dataset"):
              dataset = getattr(self, attr)
              if isinstance(dataset, list):
                  if len(dataset) > 1:
                      size = ", ".join([str(len(d)) for d in dataset])
                  else:
                      size = len(dataset[0])
              elif dataset:
                  size = len(dataset)
              else:
                  size = 0
              if attr.startswith("_"):
                  attr = attr[1:]
              message += "Size of {}{} {}= {}\n".format(
                  COLORS.IPurple, attr, COLORS.END_NO_TOKEN, size
              )
      for key, attr in self.__dict__.items():
          if key.endswith("_sampler") and attr:
              message += "{}{} {}= {}\n".format(
                  COLORS.IPurple, key, COLORS.END_NO_TOKEN, attr
              )
      message += "{}Batch size ={} {}".format(
          COLORS.IPurple, COLORS.END_NO_TOKEN, self.batch_size
      )
      return message
  
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 44 for calling the BaseDataset obj's underlying member method code with example usage: obj.__repr__() and returns: message