class_docstr: Base class for generating random augmentation parameters.
class_docstr_tok: ["Base","class","for","generating","random","augmentation","parameters","."]
code: def make_samplers(
      self, device: torch.device, dtype: torch.dtype
  ) -> None:
      raise NotImplementedError
  
imports: from typing import Any, Callable, Dict, Optional, Tuple, Type, TypeVar
  import torch
  from torch.distributions import Distribution, Uniform
  from kornia.augmentation.utils.helpers import MultiprocessWrapper
  from kornia.core import Device, Module, Tensor
label_desc: Use image node_id 5 for calling the RandomGeneratorBase obj's underlying member method code with example usage: obj.make_samplers(device, dtype) without return types