code: def serve_load_sample(self, data: str) -> Any:
      parameters = self._parameters
  
      df = pd.read_csv(StringIO(data))
      df = _pre_transform(
          df,
          parameters["numerical_fields"],
          parameters["categorical_fields"],
          parameters["codes"],
          parameters["mean"],
          parameters["std"],
      )
  
      cat_vars = _to_cat_vars_numpy(
          df, parameters["categorical_fields"]
      )
      num_vars = _to_num_vars_numpy(df, parameters["numerical_fields"])
  
      cat_vars = np.stack(cat_vars, 1)
      num_vars = np.stack(num_vars, 1)
  
      return [
          {DataKeys.INPUT: [c, n]} for c, n in zip(cat_vars, num_vars)
      ]
  
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 TabularDeserializer obj's underlying member method code with example usage: obj.serve_load_sample(data) and returns: unknown