class_docstr: An abstract base class for random datasets.
  
  Intended for subclassing, this class provides the framework for implementing
  custom random datasets. Each subclass should provide
  a concrete implementation of the `_generate_random_item` method.
  
  Attributes:
      size (int, default=100): The total number of items the dataset will contain.
docstr: Abstract method to produce a random dataset item.
  
  Subclasses must override this to define their specific random item generation.
  
  Returns:
      Dict[str, torch.Tensor]: Dictionary containing item attributes and tensors.
      The exact keys depend on the implementation of `_generate_random_item`.
docstr_tok: ["Abstract","method","to","produce","a","random","dataset","item",".","Subclasses","must","override","this","to","define","their","specific","random","item","generation",".","Returns",":","Dict","[","str",",","torch.Tensor","]",":","Dictionary","containing","item","attributes","and","tensors",".","The","exact","keys","depend","on","the","implementation","of","`","_generate_random_item","`","."]
code: def _generate_random_item(self) -> Dict[str, torch.Tensor]:
      """
      Abstract method to produce a random dataset item.
  
      Subclasses must override this to define their specific random item generation.
  
      Returns:
          Dict[str, torch.Tensor]: Dictionary containing item attributes and tensors.
          The exact keys depend on the implementation of `_generate_random_item`.
      """
      raise NotImplementedError(
          "Subclasses of AbstractRandomDataset should implement _generate_random_item."
      )
  
file_path: tnt/torchtnt/utils/data/synthetic_data.py
imports: from __future__ import annotations
  import abc
  import logging
  from dataclasses import dataclass, field
  from typing import Dict
  import torch
  from torch.utils.data import Dataset
  from torchtnt.utils.device import get_device_from_env
label_desc: Use image node_id 4 for calling the AbstractRandomDataset obj's underlying member method code with example usage: obj._generate_random_item() without return types