code: def test_distributed_spearman(self):
      batch_size = 10
      num_labels = 10
      predictions = torch.randn(batch_size, num_labels)
      labels = 0.5 * predictions + torch.randn(batch_size, num_labels)
      desired_spearman = spearman_formula(
          predictions.reshape(-1), labels.reshape(-1)
      )
      predictions = [predictions[:5], predictions[5:]]
      labels = [labels[:5], labels[5:]]
      metric_kwargs = {
          "predictions": predictions,
          "gold_labels": labels,
      }
      run_distributed_test(
          [-1, -1],
          global_distributed_metric,
          SpearmanCorrelation(),
          metric_kwargs,
          desired_spearman,
          exact=False,
      )
  
file_path: allennlp/tests/training/metrics/spearman_correlation_test.py
imports: import math
  import pytest
  import torch
  from torch.testing import assert_allclose
  from allennlp.common.testing import AllenNlpTestCase, multi_device, global_distributed_metric, run_distributed_test
  from allennlp.training.metrics import SpearmanCorrelation
label_desc: Use image node_id 4 for calling the SpearmanCorrelationTest obj's underlying member method code with example usage: obj.test_distributed_spearman() without return types