code: def __init__(
      self,
      config_to_eval,
      model,
      eval_dir,
      X,
      Y,
      X_test,
      Y_test,
      name=None,
      every_n_iter=100,
  ):
      if every_n_iter is None or every_n_iter <= 0:
          raise ValueError("invalid every_n_iter=%s." % every_n_iter)
  
      self._current_finetune = model
      self._config_to_finetune = config_to_eval
      self._name = name
      self._every_n_iter = every_n_iter
      self._timer = tf.estimator.SecondOrStepTimer(
          every_steps=every_n_iter
      )
      self._eval_dir = eval_dir
      self.train_data = (X, Y)
      self.test_data = (X_test, Y_test)
      self._iter_count = 0
  
file_path: finetune/finetune/util/in_memory_finetune.py
imports: import os
  import traceback
  import sys
  from tensorflow.core.framework import summary_pb2
  from tensorflow.python.summary.writer import writer_cache
  import tensorflow
  import numpy
label_desc: Use image node_id 1 to create a new InMemoryFinetune object from inherited base classes: tf.estimator with example: obj = InMemoryFinetune(config_to_eval, model, eval_dir, X, Y, X_test, Y_test, name, every_n_iter)