code: def forward(
      self,
      input: Tensor,
      params: Optional[List[ParamItem]] = None,
      extra_args: Dict[str, Any] = {},
  ) -> Tensor:
      self.clear_state()
  
      if params is None:
          inp = input
          _, out_shape = self.autofill_dim(inp, dim_range=(2, 4))
          params = self.forward_parameters(out_shape)
  
      input = self.transform_inputs(
          input, params=params, extra_args=extra_args
      )
  
      self._params = params
      return input
  
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 14 for calling the ImageSequentialBase obj's underlying member method code with example usage: obj.forward(input, params, extra_args) and returns: input