code: def set_dense_X(self):
      if self.storage_level != constants.StorageLevel.DISK:
          if self.dense_size_gb <= self.MAXMEMGB:
              if self.storage_level == constants.StorageLevel.SPARSE:
                  self.X = self.X.toarray()
              self.X = torch.as_tensor(
                  self.X, dtype=torch.get_default_dtype()
              )
              self.storage_level = constants.StorageLevel.DENSE
  
imports: import os
  import pickle
  import sys
  import time
  import numpy
  import scipy.sparse
  from sklearn.datasets import load_svmlight_file
  import torch
  from torch.utils.data import DataLoader, Dataset
  from torch.utils.data.dataloader import _SingleProcessDataLoaderIter, _MultiProcessingDataLoaderIter, _utils
  from .None import constants
  from .None import syssettings
label_desc: Use image node_id 3 for calling the PrepareData obj's underlying member method code with example usage: obj.set_dense_X() without return types