class_docstr: Class for managing the user data in nebullvm.
  
  Attributes:
      data_reader(Sequence): Object implementing the __getitem__, the
          __len__ and the __iter__/__next__ APIs. It should read the
          user data and return tuples of tensors for feeding the models.
code: def get_split(self, split_type="train"):
      return (
          DataManager([self[i] for i in self.train_idxs])
          if split_type == "train"
          else DataManager([self[i] for i in self.test_idxs])
      )
  
imports: from typing import Sequence, List, Tuple, Any, Union, Iterable
  import numpy
  from loguru import logger
  from nebullvm.config import MIN_DIM_INPUT_DATA
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import torch, Dataset, DataLoader
  from nebullvm.tools.onnx import convert_to_numpy
label_desc: Use image node_id 10 for calling the DataManager obj's underlying member method code with example usage: obj.get_split(split_type) and returns: unknown