code: def test_metrics_ne(second_operand, expected_result):
      """Test that `ne` operator works and returns a compositional metric."""
      first_metric = DummyMetric(2)
  
      final_ne = first_metric != second_operand
  
      assert isinstance(final_ne, CompositionalMetric)
  
      final_ne.update()
      # can't use allclose for bool tensors
      assert (expected_result == final_ne.compute()).all()
  
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 12 for calling a global function with example usage: test_metrics_ne(second_operand, expected_result) without return types