code: def test_metrics_and(second_operand, expected_result):
      """Test that `and` operator works and returns a compositional metric."""
      first_metric = DummyMetric(2)
  
      final_and = first_metric & second_operand
      final_rand = second_operand & first_metric
  
      assert isinstance(final_and, CompositionalMetric)
      assert isinstance(final_rand, CompositionalMetric)
  
      final_and.update()
      final_rand.update()
      assert torch.allclose(expected_result, final_and.compute())
      assert torch.allclose(expected_result, final_rand.compute())
  
imports: from operator import neg, pos
  from typing import Any
  import pytest
  import torch
  from torch import tensor
  from torchmetrics.metric import CompositionalMetric, Metric
label_desc: Use image node_id 2 for calling a global function with example usage: test_metrics_and(second_operand, expected_result) without return types