code: def __init__(self, input_data: DataManager, has_labels: bool = False):
      self.data = input_data
      self.has_labels = has_labels
      self.batch_size = input_data[0][0][0].shape[0]
  
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 1 to create a new PytorchDataset object from inherited base classes: Dataset with example: obj = PytorchDataset(input_data, has_labels)