code: def __getitem__(self, idx):
      inds = self.indices[
          idx * self.batch_size : (idx + 1) * self.batch_size
      ]
      batch_x = []
      df = self.df[self.cat_columns + self.cont_columns].iloc[inds]
      for cat_name in self.cat_columns:
          codes = (
              np.stack(
                  [
                      c.cat.codes.values
                      for n, c in df[[cat_name]].items()
                  ],
                  1,
              ).astype(np.int64)
              + 1
          )
          batch_x.append(codes)
      if len(self.cont_columns) > 0:
          conts = np.stack(
              [
                  c.astype("float32").values
                  for n, c in df[self.cont_columns].items()
              ],
              1,
          )
          batch_x.append(conts)
      batch_y = self.df[self.label_columns].iloc[inds].values
      batch_x = batch_x[0] if len(batch_x) == 1 else tuple(batch_x)
      return batch_x, batch_y
  
file_path: ktrain/ktrain/tabular/dataset.py
imports: from ..dataset import SequenceDataset
  from ..imports import *
label_desc: Use image node_id 3 for calling the TabularDataset obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: batch_x,  batch_y