code: def _compute(states: Dict[str, torch.Tensor]) -> torch.Tensor:
      return torch.where(
          states["calibration_denom"] <= 0.0,
          0.0,
          states["calibration_num"] / states["calibration_denom"],
      ).double()
  
file_path: torchrec/torchrec/metrics/tests/test_calibration.py
imports: import unittest
  from typing import Dict, Type
  import torch
  from torchrec.metrics.calibration import CalibrationMetric
  from torchrec.metrics.rec_metric import RecComputeMode, RecMetric
  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 TestCalibrationMetric obj's underlying member method code with example usage: obj._compute(states) and returns: torch