code: def preds_equal(self, a, b):
      assert len(a) == len(b)
      for ai, bi in zip(a, b):
          assert len(ai) == len(bi)
          for aii, bii in zip(ai, bi):
              assert aii["text"] == bii["text"]
              assert aii["start"] == bii["start"]
              assert aii["end"] == bii["end"]
              assert len(aii["confidence"]) == len(bii["confidence"])
              assert (
                  aii["confidence"].keys() == bii["confidence"].keys()
              )
              for k in aii["confidence"].keys():
                  self.assertAlmostEqual(
                      aii["confidence"][k], bii["confidence"][k]
                  )
  
imports: import unittest
  from collections import Counter
  import pytest
  import numpy
  import tensorflow
  import unicodedata
  from finetune.encoding.sequence_encoder import finetune_to_indico_sequence
  from finetune.optimizers.gradient_accumulation import get_grad_accumulation_optimizer
  from finetune.util.imbalance import compute_class_weights
  from finetune.util.optimize_loss import OPTIMIZERS
  from finetune.util.timing import ProgressBar
  from finetune.errors import FinetuneError
  from finetune import Classifier, SequenceLabeler
  from finetune.base_models.gpt.encoder import GPTEncoder
  from finetune.base_models.gpt2.encoder import GPT2Encoder
  from finetune.base_models.bert.roberta_encoder import RoBERTaEncoderV2, RoBERTaEncoder, RoBERTaEncoderSlow
  from finetune.base_models.bert.encoder import BERTEncoderMultuilingal, BERTEncoder
  from finetune.base_models.oscar.encoder import GPCEncoder
  from finetune.scheduler import Scheduler
label_desc: Use image node_id 1 for calling the TestSaveMultiple obj's underlying member method code with example usage: obj.preds_equal(a, b) without return types