code: def _input_transform_argparse_base(
      input_transform_class: Type[InputTransform],
      dataset: Optional[SupervisedDataset] = None,
      search_space_digest: Optional[SearchSpaceDigest] = None,
      input_transform_options: Optional[Dict[str, Any]] = None,
  ) -> Dict[str, Any]:
      """
      Extract the input transform kwargs from the given arguments.
  
      Args:
          input_transform_class: Input transform class.
          dataset: Dataset containing feature matrix and the response.
          search_space_digest: Search space digest.
          input_transform_options: An optional dictionary of input transform options.
              This may include overrides for the above options. For example, when
              `input_transform_class` is Normalize this dictionary might include
              {
                  "d": 2, # the dimension of the input space
              }
              See `botorch.models.transforms.input.py` for more options.
  
      Returns:
          A dictionary with input transform kwargs.
      """
      return input_transform_options or {}
  
file_path: Ax/ax/models/torch/botorch_modular/input_constructors/input_transforms.py
imports: from __future__ import annotations
  from typing import Any, Dict, Optional, Type
  import torch
  from ax.core.search_space import SearchSpaceDigest
  from ax.models.torch.utils import normalize_indices
  from ax.utils.common.typeutils import _argparse_type_encoder
  from botorch.models.transforms.input import InputPerturbation, InputTransform, Normalize, Warp
  from botorch.utils.containers import SliceContainer
  from botorch.utils.datasets import RankingDataset, SupervisedDataset
  from botorch.utils.dispatcher import Dispatcher
label_desc: Use image node_id 1 for calling a global function with example usage: _input_transform_argparse_base(input_transform_class, dataset, search_space_digest, input_transform_options) and returns: unknown