class_docstr: base class for classfication 
code: def infer(self, yield_single_examples=True):
      nn = self.create_estimator()  # pylint: disable=invalid-name
      predictions = nn.predict(
          input_fn=self.input_fn(utils.INFER),
          predict_keys=None,
          hooks=None,
          checkpoint_path=None,
          yield_single_examples=yield_single_examples,
      )
      return self.postproc_fn()(predictions, log_verbose=False)
  
imports: import os
  import re
  import functools
  import collections
  from absl import logging
  import delta.compat
  from tensorflow.python import debug
  from tensorflow.python.estimator.canned import metric_keys
  from tensorboard.plugins.pr_curve import summary
  from delta import utils
  from delta.utils.hparam import HParams
  from delta.utils import metrics
  from delta.utils import summary
  from delta.utils.register import registers
  from delta.utils.solver.base_solver import ABCEstimatorSolver
label_desc: Use image node_id 18 for calling the EstimatorSolver obj's underlying member method code with example usage: obj.infer(yield_single_examples) and returns: self