class_docstr: Policy-based image augmentation.
code: def transform_inputs(
      self,
      input: Tensor,
      params: List[ParamItem],
      extra_args: Dict[str, Any] = {},
  ) -> Tensor:
      for param in params:
          module = self.get_submodule(param.name)
          input = InputSequentialOps.transform(
              input, module=module, param=param, extra_args=extra_args
          )
          self._update_transform_matrix_by_module(module)
      return input
  
imports: from typing import Any, Dict, Iterator, List, Optional, Tuple, Union, cast
  import torch
  from kornia.augmentation.auto.operations.base import OperationBase
  from kornia.augmentation.auto.operations.policy import PolicySequential
  from kornia.augmentation.container.base import ImageSequentialBase, TransformMatrixMinIn
  from kornia.augmentation.container.ops import InputSequentialOps
  from kornia.augmentation.container.params import ParamItem
  from kornia.core import Module, Tensor
  from kornia.utils import eye_like
label_desc: Use image node_id 10 for calling the PolicyAugmentBase obj's underlying member method code with example usage: obj.transform_inputs(input, params, extra_args) and returns: input