code: def _compute_score(self, x, feat, feat_type):
      if feat_type == "onehot":
          return (np.argmax(x[feat].to_numpy(), axis=1) + 1) / len(feat)
      else:
          return (
              np.ones(len(x))
              if x[feat].max() == 0
              else x[feat].values / x[feat].max()
          )
  
imports: import pytest
  import joblib
  import os
  import json
  import numpy
  import pandas
  from itertools import product
  import matplotlib
  from abc import ABC, abstractmethod
  import warnings
label_desc: Use image node_id 3 for calling the DummyModel obj's underlying member method code with example usage: obj._compute_score(x, feat, feat_type) and returns: unknown, unknown