class_docstr: base class for classfication 
docstr: return input_fn 
docstr_tok: ["return","input_fn"]
code: def input_fn(self, mode):
      """return input_fn"""
      super().input_fn(mode)
      batch_size = self.config["solver"]["optimizer"]["batch_size"]
      num_epoch = self.config["solver"]["optimizer"]["epochs"]
      return self.task.input_fn(mode, batch_size, num_epoch)
  
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 2 for calling the EstimatorSolver obj's underlying member method code with example usage: obj.input_fn(mode) and returns: self