class_docstr: Prepare categorical data for the model specified by "prefix".
  For multiple models requiring categorical data, we need to create a CategoricalProcessor
  for each related model so that they will have independent input.
docstr: Parameters
  ----------
  model
      The model for which this processor would be created.
  requires_column_info
      Whether to require feature column information in dataloader.
code: def __init__(
      self,
      model: nn.Module,
      requires_column_info: bool = False,
  ):
      """
      Parameters
      ----------
      model
          The model for which this processor would be created.
      requires_column_info
          Whether to require feature column information in dataloader.
      """
      self.prefix = model.prefix
      self.requires_column_info = requires_column_info
  
file_path: autogluon/multimodal/src/autogluon/multimodal/data/process_categorical.py
imports: from typing import Any, Dict, List, Optional, Union
  import numpy
  from torch import nn
  from ..constants import CATEGORICAL, COLUMN
  from .collator import StackCollator, TupleCollator
label_desc: Use image node_id 1 to create a new CategoricalProcessor object  with example: obj = CategoricalProcessor(model, requires_column_info)