code: def step(self, model: Model, trace_logger: TraceLogger):
      step_result = defaultdict(list)
      likelihoods = []
      probs = []
      for step_kind, step in self.schedule.steps(model):
          result = step()
          if type(result) == tuple:
              result, likelihood, prob = result
              likelihoods.append(likelihood)
              probs.append(prob)
          log_message = trace_logger[step_kind](result)
          if log_message is not None:
              step_result[step_kind].append(log_message)
      return (
          {
              x: np.mean([1 if y else 0 for y in step_result[x]])
              for x in step_result
          },
          likelihoods,
          probs,
      )
  
file_path: imodels/imodels/experimental/bartpy/samplers/modelsampler.py
imports: import copy
  from collections import defaultdict
  from typing import List, Mapping, Union, Any, Type
  import numpy
  from tqdm import tqdm
  from ..model import Model
  from ..samplers.sampler import Sampler
  from ..samplers.schedule import SampleSchedule
  from ..trace import TraceLogger
label_desc: Use image node_id 2 for calling the ModelSampler obj's underlying member method code with example usage: obj.step(model, trace_logger) and returns: unknown,  likelihoods,  probs