code: def set_tagger_decoder_parameters(config: "ModelConfig") -> None:
      """Overrides the reduce_input parameter for text and sequence output features when a tagger decoder is used.
      This is done to ensure that the decoder correctly gets a 3D tensor as input.
  
      Returns:
          None -> modifies output_features
      """
      for output_feature in config.output_features:
          if (
              output_feature.type in {TEXT, SEQUENCE}
              and output_feature.decoder.type == "tagger"
          ):
              if output_feature.reduce_input is not None:
                  warnings.warn(
                      "reduce_input must be set to `None` when using a tagger decoder for your output feature. "
                      f"Setting reduce_input to `None` for `{output_feature.name}`."
                  )
                  output_feature.reduce_input = None
  
imports: import copy
  import logging
  import sys
  import warnings
  from typing import Any, Dict, List, Mapping, Set, TYPE_CHECKING
  from marshmallow import ValidationError
  from transformers import AutoConfig
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import CATEGORY, COMBINED, DECODER, DEFAULTS, ENCODER, GRID_SEARCH, INPUT_FEATURES, LOSS, MODEL_ECD, MODEL_LLM, OUTPUT_FEATURES, PARAMETERS, PREPROCESSING, SEQUENCE, SPACE, TEXT, TYPE
  from ludwig.features.feature_utils import compute_feature_hash
  from ludwig.schema.features.utils import output_config_registry
  from ludwig.schema.hyperopt.scheduler import BaseHyperbandSchedulerConfig
  from ludwig.schema.llms.generation import LLMGenerationConfig
  from ludwig.schema.trainer import ECDTrainerConfig
  from ludwig.types import HyperoptConfigDict, ModelConfigDict
  from ludwig.utils.data_utils import get_sanitized_feature_name
  from ludwig.utils.llm_utils import get_context_len
label_desc: Use image node_id 11 for calling a global function with example usage: set_tagger_decoder_parameters(config) without return types