code: def _array_with_string_indices_to_dict(
      rows: List[str], cols: List[str], A: np.ndarray
  ) -> Dict[str, Dict[str, np.ndarray]]:
      """
      Args:
          - rows: A list of strings with which to index rows of A.
          - cols: A list of strings with which to index columns of A.
          - A: A matrix, with `len(rows)` rows and `len(cols)` columns.
  
      Returns:
          A dictionary dict that satisfies dict[rows[i]][cols[j]] = A[i, j].
      """
      return {r: dict(zip(cols, a)) for r, a in zip(rows, A)}
  
imports: from copy import deepcopy
  from typing import Any, Callable, Dict, List, Optional, Union
  import numpy
  import torch
  from ax.modelbridge.torch import TorchModelBridge
  from ax.models.torch.botorch import BotorchModel
  from ax.models.torch.botorch_modular.model import BoTorchModel
  from ax.utils.common.typeutils import checked_cast
  from botorch.models.model import Model, ModelList
  from botorch.posteriors.gpytorch import GPyTorchPosterior
  from botorch.sampling.normal import SobolQMCNormalSampler
  from botorch.utils.sampling import draw_sobol_samples
  from botorch.utils.transforms import unnormalize
  from torch import Tensor
label_desc: Use image node_id 7 for calling a global function with example usage: _array_with_string_indices_to_dict(rows, cols, A) and returns: unknown