code: def _raw_values_to_model_predict_arm(
      values: Dict[str, Tuple[float, float]]
  ) -> TModelPredictArm:
      return (
          {k: v[0] for k, v in values.items()},  # v[0] is mean
          {
              k: {k: v[1] * v[1]} for k, v in values.items()
          },  # v[1] is sem
      )
  
imports: from collections import OrderedDict
  from functools import reduce
  from logging import Logger
  from typing import Dict, Iterable, List, Optional, Tuple, Type
  import pandas
  import torch
  from ax.core.base_trial import TrialStatus
  from ax.core.batch_trial import BatchTrial
  from ax.core.data import Data
  from ax.core.experiment import Experiment
  from ax.core.generator_run import GeneratorRun
  from ax.core.objective import MultiObjective, Objective, ScalarizedObjective
  from ax.core.observation import Observation
  from ax.core.optimization_config import MultiObjectiveOptimizationConfig, OptimizationConfig
  from ax.core.outcome_constraint import ObjectiveThreshold, OutcomeConstraint
  from ax.core.trial import Trial
  from ax.core.types import ComparisonOp, TModelPredictArm, TParameterization
  from ax.exceptions.core import UnsupportedError, UserInputError
  from ax.modelbridge.base import ModelBridge
  from ax.modelbridge.cross_validation import assess_model_fit, compute_diagnostics, cross_validate
  from ax.modelbridge.generation_strategy import GenerationStrategy
  from ax.modelbridge.modelbridge_utils import observed_pareto_frontier, predicted_pareto_frontier
  from ax.modelbridge.registry import get_model_from_generator_run, ModelRegistryBase, Models
  from ax.modelbridge.torch import TorchModelBridge
  from ax.modelbridge.transforms.utils import derelativize_optimization_config_with_raw_status_quo
  from ax.plot.pareto_utils import get_tensor_converter_model
  from ax.utils.common.logger import get_logger
  from ax.utils.common.typeutils import checked_cast, not_none
  from numpy import NaN
  from torch import Tensor
label_desc: Use image node_id 4 for calling a global function with example usage: _raw_values_to_model_predict_arm(values) and returns: unknown,  unknown