code: def test_data(request):
      return [
          # Multiclass input data of shape (N, )
          (
              torch.rand(10, 4),
              torch.randint(0, 4, size=(10,)).long(),
              4,
              1,
          ),
          (
              torch.rand(4, 10),
              torch.randint(0, 10, size=(4,)).long(),
              10,
              1,
          ),
          (
              torch.rand(4, 2),
              torch.randint(0, 2, size=(4,)).long(),
              2,
              1,
          ),
          (
              torch.rand(100, 5),
              torch.randint(0, 5, size=(100,)).long(),
              5,
              16,
          ),
          # Multiclass input data of shape (N, L)
          (
              torch.rand(10, 4, 5),
              torch.randint(0, 4, size=(10, 5)).long(),
              4,
              1,
          ),
          (
              torch.rand(4, 10, 5),
              torch.randint(0, 10, size=(4, 5)).long(),
              10,
              1,
          ),
          (
              torch.rand(100, 9, 7),
              torch.randint(0, 9, size=(100, 7)).long(),
              9,
              16,
          ),
          # Multiclass input data of shape (N, H, W, ...)
          (
              torch.rand(4, 5, 12, 10),
              torch.randint(0, 5, size=(4, 12, 10)).long(),
              5,
              1,
          ),
          (
              torch.rand(4, 5, 10, 12, 8),
              torch.randint(0, 5, size=(4, 10, 12, 8)).long(),
              5,
              1,
          ),
          (
              torch.rand(100, 3, 8, 8),
              torch.randint(0, 3, size=(100, 8, 8)).long(),
              3,
              16,
          ),
      ][request.param]
  
imports: import os
  import numpy
  import pytest
  import torch
  from sklearn.metrics import accuracy_score, confusion_matrix, precision_score, recall_score
  import ignite.distributed
  from ignite.exceptions import NotComputableError
  from ignite.metrics import ConfusionMatrix, IoU, JaccardIndex, mIoU
  from ignite.metrics.confusion_matrix import cmAccuracy, cmPrecision, cmRecall, DiceCoefficient
label_desc: Use image node_id 4 for calling a global function with example usage: test_data(request) and returns: list