class_docstr: GeometricAugmentationBase2D base class for customized geometric augmentation implementations.
  
  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``.
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docstr: Perform inverse operations.
  
  Args:
      input: the input tensor.
      params: the corresponding parameters for an operation.
          If None, a new parameter suite will be generated.
      **kwargs: key-value pairs to override the parameters and flags.
docstr_tok: ["Perform","inverse","operations",".","Args",":","input",":","the","input","tensor",".","params",":","the","corresponding","parameters","for","an","operation",".","If","None",",","a","new","parameter","suite","will","be","generated",".","*","*","kwargs",":","key-value","pairs","to","override","the","parameters","and","flags","."]
code: def inverse(
      self,
      input: Tensor,
      params: Optional[Dict[str, Tensor]] = None,
      **kwargs: Any,
  ) -> Tensor:
      """Perform inverse operations.
  
      Args:
          input: the input tensor.
          params: the corresponding parameters for an operation.
              If None, a new parameter suite will be generated.
          **kwargs: key-value pairs to override the parameters and flags.
      """
      input_shape = input.shape
      in_tensor = self.transform_tensor(input)
  
      params, flags = self._process_kwargs_to_params_and_flags(
          self._params if params is None else params,
          self.flags,
          **kwargs,
      )
  
      if params is None:
          params = self._params
      transform = self.get_transformation_matrix(
          in_tensor, params=params, flags=flags
      )
  
      transform = self.compute_inverse_transformation(transform)
      output = self.inverse_inputs(in_tensor, params, flags, transform)
  
      if self.keepdim:
          return self.transform_output_tensor(output, input_shape)
  
      return output
  
imports: from typing import Any, Dict, Optional, Tuple
  from kornia.augmentation._2d.base import RigidAffineAugmentationBase2D
  from kornia.constants import Resample
  from kornia.core import Tensor, as_tensor
  from kornia.geometry.boxes import Boxes
  from kornia.geometry.keypoints import Keypoints
  from kornia.utils.helpers import _torch_inverse_cast
label_desc: Use image node_id 17 for calling the GeometricAugmentationBase2D obj's underlying member method code with example usage: obj.inverse(input, params) and returns: output, self