code: def get_stats_dtypes_shapes_from_steps(
      steps: Iterable[BlockedStep],
  ) -> Dict[str, Tuple[StatDtype, StatShape]]:
      """Combines stats dtype shape dictionaries from multiple step methods.
  
      In the resulting stats dict, each sampler stat is prefixed by `sampler_#__`.
      """
      result = {}
      for s, step in enumerate(steps):
          for sname, (dtype, shape) in step.stats_dtypes_shapes.items():
              result[flat_statname(s, sname)] = (dtype, shape)
      return result
  
imports: import warnings
  from abc import ABC, abstractmethod
  from enum import IntEnum, unique
  from typing import Any, Dict, Iterable, List, Mapping, Sequence, Tuple, Union
  import numpy
  from pytensor.graph.basic import Variable
  from pymc.blocking import PointType, StatDtype, StatsDict, StatShape, StatsType
  from pymc.model import modelcontext
label_desc: Use image node_id 3 for calling a global function with example usage: get_stats_dtypes_shapes_from_steps(steps) and returns: result