code: def convert_str_to_rv_dict(
      model, start: StartDict
  ) -> Dict[TensorVariable, Optional[Union[np.ndarray, Variable, str]]]:
      """Helper function for converting a user-provided start dict with str keys of (transformed) variable names
      to a dict mapping the RV tensors to untransformed initvals.
      TODO: Deprecate this functionality and only accept TensorVariables as keys
      """
      initvals = {}
      for key, initval in start.items():
          if isinstance(key, str):
              if is_transformed_name(key):
                  rv = model[get_untransformed_name(key)]
                  initvals[rv] = model.rvs_to_transforms[rv].backward(
                      initval, *rv.owner.inputs
                  )
              else:
                  initvals[model[key]] = initval
          else:
              initvals[key] = initval
      return initvals
  
file_path: pymc/pymc/initial_point.py
imports: import functools
  import warnings
  from typing import Callable, Dict, List, Optional, Sequence, Set, Union
  import numpy
  import pytensor
  import pytensor.tensor
  from pytensor.graph.basic import Variable
  from pytensor.graph.fg import FunctionGraph
  from pytensor.tensor.variable import TensorVariable
  from pymc.logprob.transforms import Transform
  from pymc.pytensorf import compile_pymc, find_rng_nodes, replace_rng_nodes, reseed_rngs
  from pymc.util import get_transformed_name, get_untransformed_name, is_transformed_name
label_desc: Use image node_id 1 for calling a global function with example usage: convert_str_to_rv_dict(model, start) and returns: initvals