code: def run(self, trial: BaseTrial) -> Dict[str, Any]:
      self.statuses[trial.index] = TrialStatus.COMPLETED
      preds = {  # Cache predictions for each arm
          arm.name: self.surrogate.predict(
              X=torch.tensor(
                  [
                      *self._get_transformed_parameters(
                          arm.parameters
                      ).values()
                  ]
              ).reshape([1, len(arm.parameters)])
          )[0].squeeze(0)
          for arm in trial.arms
      }
      return {
          metric_name: {
              arm_name: float(pred[i])
              for arm_name, pred in preds.items()
          }
          for i, metric_name in enumerate(self.metric_names)
      }
  
imports: from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple
  import pandas
  import torch
  from ax.benchmark.benchmark_problem import BenchmarkProblemBase
  from ax.core.base_trial import BaseTrial, TrialStatus
  from ax.core.data import Data
  from ax.core.metric import Metric, MetricFetchE, MetricFetchResult
  from ax.core.observation import ObservationFeatures
  from ax.core.optimization_config import MultiObjectiveOptimizationConfig, OptimizationConfig
  from ax.core.parameter import RangeParameter
  from ax.core.runner import Runner
  from ax.core.search_space import SearchSpace
  from ax.core.types import TParameterization
  from ax.modelbridge.transforms.int_to_float import IntToFloat
  from ax.modelbridge.transforms.log import Log
  from ax.models.torch.botorch_modular.surrogate import Surrogate
  from ax.utils.common.base import Base
  from ax.utils.common.equality import equality_typechecker
  from ax.utils.common.result import Err, Ok
  from ax.utils.common.serialization import TClassDecoderRegistry, TDecoderRegistry
  from ax.utils.common.typeutils import not_none
  from botorch.utils.datasets import SupervisedDataset
label_desc: Use image node_id 3 for calling the SurrogateRunner obj's underlying member method code with example usage: obj.run(trial) and returns: unknown