docstr: Same as in .fit()
  :return: np.array (n_test, n_classes) with class probability estimates 
docstr_tok: ["Same","as","in",".fit","(",")",":","return",":","np.array","(","n_test",",","n_classes",")","with","class","probability","estimates"]
code: def predict(self, x=None):
      """Same as in .fit()
      :return: np.array (n_test, n_classes) with class probability estimates
      """
      if self.tempscale:
          return t_softmax(self.prediction_cache, t=0.5)
      else:
          return self.prediction_cache
  
imports: import abc
  from typing import Dict
  import numpy
  from sklearn.base import BaseEstimator
  from lightwood.analysis.nc.util import t_softmax
label_desc: Use image node_id 3 for calling the CachedClassifierAdapter obj's underlying member method code with example usage: obj.predict(x) and returns: t_softmax, self