code: def _get_unique_classes(true, predicted):
      true_and_pred = list(true) + list(predicted)
      return list(
          set([seq["label"] for seqs in true_and_pred for seq in seqs])
      )
  
imports: import os
  import copy
  from functools import partial
  from collections import defaultdict, OrderedDict
  import numpy
  from sklearn.metrics import confusion_matrix
  from tensorflow.python.platform import gfile
  from tensorflow.python.summary import summary_iterator
  import tabulate
  from finetune.encoding.input_encoder import get_spacy
label_desc: Use image node_id 1 for calling a global function with example usage: _get_unique_classes(true, predicted) and returns: list