class_docstr: Base class for generating random augmentation parameters.
class_docstr_tok: ["Base","class","for","generating","random","augmentation","parameters","."]
code: def to(self, *args: Any, **kwargs: Any) -> "RandomGeneratorBase":
      (
          device,
          dtype,
          non_blocking,
          convert_to_format,
      ) = torch._C._nn._parse_to(*args, **kwargs)
      self.set_rng_device_and_dtype(device=device, dtype=dtype)
      return self
  
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 4 for calling the RandomGeneratorBase obj's underlying member method code with example usage: obj.to() and returns: self