code: def test_fit_predict_doc_rep(self):
      model = DocumentLabeler(
          n_epochs=20, base_model=DocRep, crf_sequence_labeling=True
      )
      model.fit(self.documents, self.labels)
      preds = model.predict(self.documents)
      self.assertEqual(len(preds), len(self.documents))
      for pred, lab in zip(preds, self.labels):
          # checks that an overfit model, will produce the exact same output as was given as
          # input even after being sliced up and put back together.
          print(pred, lab)
          for p, l in zip(pred, lab):
              del p["confidence"]
              self.assertEqual(p, l)
  
file_path: finetune/tests/test_document.py
imports: import os
  import json
  import unittest
  import pandas
  from sklearn.model_selection import train_test_split
  from finetune import DocumentLabeler
  from finetune.base_models import DocRep
  from finetune.util.metrics import sequence_labeling_micro_token_f1
label_desc: Use image node_id 3 for calling the TestDocumentLabeler obj's underlying member method code with example usage: obj.test_fit_predict_doc_rep() without return types