code: def _upgrade_feature(feature: FeatureConfigDict) -> FeatureConfigDict:
      """Upgrades feature config (in-place)"""
      if feature.get(TYPE) == "numerical":
          warnings.warn(
              'Feature type "numerical" renamed to "number" and will be removed in v0.6',
              DeprecationWarning,
          )
          feature[TYPE] = NUMBER
      if feature.get(TYPE) == AUDIO:
          if PREPROCESSING in feature:
              feature[PREPROCESSING] = upgrade_audio_preprocessing(
                  feature[PREPROCESSING]
              )
          warnings.warn(
              "Parameters specified at the `audio_feature` parameter level have been unnested and should now "
              "be specified at the preprocessing level. Support for `audio_feature` will be removed in v0.7",
              DeprecationWarning,
          )
      return feature
  
imports: import copy
  import logging
  import warnings
  from typing import Any, Callable, Dict, List, Union
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import AUDIO, BIAS, CLASS_WEIGHTS, COLUMN, CONV_BIAS, CONV_USE_BIAS, DECODER, DEFAULT_BIAS, DEFAULT_USE_BIAS, DEFAULTS, ENCODER, EVAL_BATCH_SIZE, EXECUTOR, FORCE_SPLIT, HEIGHT, HYPEROPT, IMAGE, INPUT_FEATURES, LOSS, MISSING_VALUE_STRATEGY, MODEL_ECD, MODEL_GBM, MODEL_TYPE, NAME, NUM_SAMPLES, NUMBER, OUTPUT_FEATURES, PARAMETERS, PREPROCESSING, PROBABILITIES, RANDOM, RAY, SAMPLER, SCHEDULER, SEARCH_ALG, SEQUENCE, SPLIT, SPLIT_PROBABILITIES, STRATIFY, TEXT, TIMESERIES, TRAINER, TRAINING, TYPE, USE_BIAS, WIDTH
  from ludwig.features.feature_registries import get_base_type_registry, get_input_type_registry, get_output_type_registry
  from ludwig.globals import LUDWIG_VERSION
  from ludwig.schema.defaults.gbm import GBMDefaultsConfig
  from ludwig.schema.encoders.utils import get_encoder_cls
  from ludwig.types import FeatureConfigDict, FeatureTypeDefaultsDict, HyperoptConfigDict, ModelConfigDict, PreprocessingConfigDict, TrainerConfigDict, TrainingSetMetadataDict
  from ludwig.utils.metric_utils import TrainerMetric
  from ludwig.utils.misc_utils import get_from_registry, merge_dict
  from ludwig.utils.version_transformation import VersionTransformation, VersionTransformationRegistry
label_desc: Use image node_id 10 for calling a global function with example usage: _upgrade_feature(feature) and returns: feature