class_docstr: This set of tests verify the computation logic of AUPRC in several
  corner cases that we know the computation results. The goal is to
  provide some confidence of the correctness of the math formula.
code: def test_grouped_auprc(self) -> None:
      test_data = generate_model_outputs_cases()
      for inputs in test_data:
          try:
              self._test_grouped_auprc_helper(**inputs)
          except AssertionError:
              print("Assertion error caught with data set ", inputs)
              raise
  
imports: import unittest
  from typing import Dict, Iterable, List, Optional, Type, Union
  import torch
  from torch import no_grad
  from torchrec.metrics.auprc import _compute_auprc_helper, AUPRCMetric
  from torchrec.metrics.metrics_config import DefaultTaskInfo
  from torchrec.metrics.rec_metric import RecComputeMode, RecMetric, RecMetricException, RecTaskInfo
  from torchrec.metrics.test_utils import metric_test_helper, rec_metric_value_test_launcher, TestMetric
label_desc: Use image node_id 2 for calling the GroupedAUPRCValueTest obj's underlying member method code with example usage: obj.test_grouped_auprc() without return types