code: def test_top_1_accuracy(self):
      labels = torch.tensor([0, 0, 2], dtype=torch.long)
  
      accuracy = TopKClassificationAccuracy(top_k=None)
      acc = accuracy(logits=self.top_k_logits, labels=labels)
  
      assert accuracy.correct_counts_k.shape == torch.Size([1])
      assert accuracy.total_counts_k.shape == torch.Size([1])
      assert abs(acc[0] - 0.667) < 1e-3
  
imports: import pytest
  import torch
  from nemo.collections.common.metrics.classification_accuracy import TopKClassificationAccuracy
  from nemo.collections.common.metrics.punct_er import DatasetPunctuationErrorRate, OccurancePunctuationErrorRate, punctuation_error_rate
  from .loss_inputs import ALL_NUM_MEASUREMENTS_ARE_ZERO, NO_ZERO_NUM_MEASUREMENTS, SOME_NUM_MEASUREMENTS_ARE_ZERO
  from .perplexity_inputs import NO_PROBS_NO_LOGITS, ONLY_LOGITS1, ONLY_LOGITS100, ONLY_PROBS, PROBS_AND_LOGITS
  from .pl_utils import LossTester, PerplexityTester
label_desc: Use image node_id 1 for calling the TestCommonMetrics obj's underlying member method code with example usage: obj.test_top_1_accuracy() without return types