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 from_iterable(cls, iterable: Iterable, max_length: int = 500):
      return cls([x for i, x in enumerate(iterable) if i < max_length])
  
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 8 for calling the DataManager obj's underlying member method code with example usage: obj.from_iterable(cls, iterable, max_length) and returns: cls