code: def compute_parameters(
      train_data_frame: DataFrame,
      numerical_fields: List[str],
      categorical_fields: List[str],
  ) -> Dict[str, Any]:
      mean, std = _compute_normalization(
          train_data_frame, numerical_fields
      )
  
      codes = _generate_codes(train_data_frame, categorical_fields)
  
      return {
          "mean": mean,
          "std": std,
          "codes": codes,
          "numerical_fields": numerical_fields,
          "categorical_fields": categorical_fields,
      }
  
file_path: lightning-flash/src/flash/tabular/input.py
imports: from io import StringIO
  from typing import Any, Dict, List, Optional, Union
  import numpy
  from flash.core.data.io.input import DataKeys, Input, ServeInput
  from flash.core.utilities.imports import _PANDAS_AVAILABLE
  from flash.tabular.classification.utils import _compute_normalization, _generate_codes, _pre_transform, _to_cat_vars_numpy, _to_num_vars_numpy
label_desc: Use image node_id 2 for calling the TabularDataFrameInput obj's underlying member method code with example usage: obj.compute_parameters(train_data_frame, numerical_fields, categorical_fields) and returns: dict