class_docstr: Enables computation matrix computation.
class_docstr_tok: ["Enables","computation","matrix","computation","."]
code: def _update_transform_matrix_by_module(self, module: Module) -> None:
      if self._transformation_matrix_arg == "skip":
          return
      if isinstance(module, self._valid_ops_for_transform_computation):
          self._update_transform_matrix_for_valid_op(module)
      elif self._transformation_matrix_arg == "rigid":
          raise RuntimeError(
              f"Non-rigid module `{module}` is not supported under `rigid` computation mode. "
              "Please either update the module or change the `transformation_matrix` argument."
          )
  
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 5 for calling the TransformMatrixMinIn obj's underlying member method code with example usage: obj._update_transform_matrix_by_module(module) without return types