code: def transform(
      cls,
      input: Tensor,
      module: Module,
      param: ParamItem,
      extra_args: Dict[str, Any] = {},
  ) -> Tensor:
      if isinstance(
          module, (_AugmentationBase, K.MixAugmentationBaseV2)
      ):
          input = module(
              input,
              params=cls.get_instance_module_param(param),
              data_keys=[DataKey.INPUT],
              **extra_args,
          )
      elif isinstance(module, (K.container.ImageSequentialBase,)):
          input = module.transform_inputs(
              input,
              params=cls.get_sequential_module_param(param),
              extra_args=extra_args,
          )
      elif isinstance(module, (K.auto.operations.OperationBase,)):
          input = module(
              input, params=cls.get_instance_module_param(param)
          )
      else:
          if param.data is not None:
              raise AssertionError(
                  f"Non-augmentaion operation {param.name} require empty parameters. Got {param}."
              )
          input = module(input)
      return input
  
imports: from abc import ABCMeta, abstractmethod
  from typing import Any, Callable, Dict, Generic, List, Optional, Type, TypeVar, Union
  from typing_extensions import ParamSpec
  import kornia.augmentation
  from kornia.augmentation.base import _AugmentationBase
  from kornia.constants import DataKey
  from kornia.core import Module, Tensor
  from kornia.geometry.boxes import Boxes
  from kornia.geometry.keypoints import Keypoints
  from .params import ParamItem
label_desc: Use image node_id 1 for calling the InputSequentialOps obj's underlying member method code with example usage: obj.transform(cls, input, module, param, extra_args) and returns: input