class_docstr: Managed optimization loop, in which Ax oversees deployment of trials and
  gathering data.
class_docstr_tok: ["Managed","optimization","loop",",","in","which","Ax","oversees","deployment","of","trials","and","gathering","data","."]
code: def _get_weights_by_arm(
      self, trial: BaseTrial
  ) -> Iterable[Tuple[Arm, Optional[float]]]:
      if isinstance(trial, Trial):
          if trial.arm is not None:
              return [(not_none(trial.arm), None)]
          return []
      elif isinstance(trial, BatchTrial):
          return trial.normalized_arm_weights().items()
      else:
          raise UserInputError(f"Invalid trial type: {type(trial)}")
  
imports: from __future__ import annotations
  import inspect
  import logging
  from typing import Iterable, List, Optional, Tuple
  from ax.core.arm import Arm
  from ax.core.base_trial import BaseTrial
  from ax.core.batch_trial import BatchTrial
  from ax.core.experiment import Experiment
  from ax.core.formatting_utils import data_and_evaluations_from_raw_data
  from ax.core.trial import Trial
  from ax.core.types import TEvaluationFunction, TEvaluationOutcome, TModelPredictArm, TParameterization
  from ax.core.utils import get_pending_observation_features
  from ax.exceptions.constants import CHOLESKY_ERROR_ANNOTATION
  from ax.exceptions.core import SearchSpaceExhausted, UserInputError
  from ax.modelbridge.base import ModelBridge
  from ax.modelbridge.dispatch_utils import choose_generation_strategy
  from ax.modelbridge.generation_strategy import GenerationStrategy
  from ax.modelbridge.registry import Models
  from ax.service.utils.best_point import get_best_parameters_from_model_predictions, get_best_raw_objective_point
  from ax.service.utils.instantiation import InstantiationBase, TParameterRepresentation
  from ax.utils.common.executils import retry_on_exception
  from ax.utils.common.logger import get_logger
  from ax.utils.common.typeutils import not_none
label_desc: Use image node_id 6 for calling the OptimizationLoop obj's underlying member method code with example usage: obj._get_weights_by_arm(trial) and returns: list, list, trial