class_docstr: AugmentationBase2D base class for rigid/affine augmentation implementations.
  
  RigidAffineAugmentationBase2D enables routined transformation with given transformation matrices
  for different data types like masks, boxes, and keypoints.
  
  Args:
      p: probability for applying an augmentation. This param controls the augmentation probabilities
        element-wise for a batch.
      p_batch: probability for applying an augmentation to a batch. This param controls the augmentation
        probabilities batch-wise.
      same_on_batch: apply the same transformation across the batch.
      keepdim: whether to keep the output shape the same as input ``True`` or broadcast it to the batch
        form ``False``.
class_docstr_tok: ["AugmentationBase2D","base","class","for","rigid\/affine","augmentation","implementations",".","RigidAffineAugmentationBase2D","enables","routined","transformation","with","given","transformation","matrices","for","different","data","types","like","masks",",","boxes",",","and","keypoints",".","Args",":","p",":","probability","for","applying","an","augmentation",".","This","param","controls","the","augmentation","probabilities","element-wise","for","a","batch",".","p_batch",":","probability","for","applying","an","augmentation","to","a","batch",".","This","param","controls","the","augmentation","probabilities","batch-wise",".","same_on_batch",":","apply","the","same","transformation","across","the","batch",".","keepdim",":","whether","to","keep","the","output","shape","the","same","as","input","``","True","``","or","broadcast","it","to","the","batch","form","``","False","``","."]
code: def inverse_boxes(
      self,
      input: Boxes3D,
      params: Dict[str, Tensor],
      flags: Dict[str, Any],
      transform: Optional[Tensor] = None,
  ) -> Boxes3D:
      raise NotImplementedError
  
imports: from typing import Any, Dict, Optional
  from torch import float16, float32, float64
  import kornia
  from kornia.augmentation.base import _AugmentationBase
  from kornia.augmentation.utils import _transform_input3d, _validate_input_dtype
  from kornia.core import Tensor
  from kornia.geometry.boxes import Boxes3D
  from kornia.geometry.keypoints import Keypoints3D
label_desc: Use image node_id 6 for calling the RigidAffineAugmentationBase3D obj's underlying member method code with example usage: obj.inverse_boxes(input, params, flags, transform) without return types