class_docstr: Test class for `PermutationInvariantTraining` metric.
class_docstr_tok: ["Test","class","for","`","PermutationInvariantTraining","`","metric","."]
docstr: Test dtype support of the metric on CPU.
docstr_tok: ["Test","dtype","support","of","the","metric","on","CPU","."]
code: def test_pit_half_cpu(
      self, preds, target, ref_metric, metric_func, mode, eval_func
  ):
      """Test dtype support of the metric on CPU."""
      pytest.xfail("PIT metric does not support cpu + half precision")
  
imports: from functools import partial
  from typing import Callable, Tuple
  import numpy
  import pytest
  import torch
  from scipy.optimize import linear_sum_assignment
  from torch import Tensor
  from torchmetrics.audio import PermutationInvariantTraining
  from torchmetrics.functional.audio import permutation_invariant_training, scale_invariant_signal_distortion_ratio, signal_noise_ratio
  from torchmetrics.functional.audio.pit import _find_best_perm_by_exhaustive_method, _find_best_perm_by_linear_sum_assignment
  from unittests import BATCH_SIZE, NUM_BATCHES, _Input
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 4 for calling the TestPIT obj's underlying member method code with example usage: obj.test_pit_half_cpu(preds, target, ref_metric, metric_func, mode, eval_func) without return types