docstr: Compute the transformation matrix according to the provided parameters.
  
  Args:
      input: the input tensor.
      params: params for the sequence.
      recompute: if to recompute the transformation matrix according to the params.
          default: False.
code: def get_transformation_matrix(
      self,
      input: Tensor,
      params: Optional[List[ParamItem]] = None,
      recompute: bool = False,
      extra_args: Dict[str, Any] = {},
  ) -> Optional[Tensor]:
      """Compute the transformation matrix according to the provided parameters.
  
      Args:
          input: the input tensor.
          params: params for the sequence.
          recompute: if to recompute the transformation matrix according to the params.
              default: False.
      """
      raise NotImplementedError
  
imports: from collections import OrderedDict
  from itertools import zip_longest
  from typing import Any, Dict, Iterator, List, Optional, Tuple
  import torch
  from torch import nn
  import kornia.augmentation
  from kornia.augmentation.base import _AugmentationBase
  from kornia.core import Module, Tensor
  from kornia.geometry.boxes import Boxes
  from kornia.geometry.keypoints import Keypoints
  from .ops import BoxSequentialOps, InputSequentialOps, KeypointSequentialOps, MaskSequentialOps
  from .params import ParamItem
label_desc: Use image node_id 2 for calling the ImageSequentialBase obj's underlying member method code with example usage: obj.get_transformation_matrix(input, params, recompute, extra_args) without return types