code: def on_epoch_end(self, args, state, control, **kwargs):
      if control.should_evaluate:
          control_copy = deepcopy(control)
          self._trainer.evaluate(
              eval_dataset=self._trainer.train_dataset,
              metric_key_prefix="train",
          )
          return control_copy
  
file_path: transformers/examples/research_projects/codeparrot/examples/train_complexity_predictor.py
imports: import argparse
  from copy import deepcopy
  import numpy
  from datasets import ClassLabel, DatasetDict, load_dataset
  from evaluate import load
  from transformers import AutoModelForSequenceClassification, AutoTokenizer, DataCollatorWithPadding, Trainer, TrainerCallback, TrainingArguments, set_seed
label_desc: Use image node_id 2 for calling the CustomCallback obj's underlying member method code with example usage: obj.on_epoch_end(args, state, control) and returns: control_copy