code: def test_window_metric(self) -> None:
      ne = NEMetric(
          world_size=1,
          my_rank=0,
          batch_size=128,
          tasks=[DefaultTaskInfo],
          window_size=3 * 128,
      )
      # Mimic the case where the metric module is moved to GPU.
      device = torch.device("cuda:0")
      ne.to(device)
  
      ne_computation = ne._metrics_computations[0]
      # test RecMetricComputation._add_window_state
      torch.allclose(
          ne_computation.window_cross_entropy_sum,
          torch.tensor([0.0], dtype=torch.double, device=device),
      )
      torch.allclose(
          ne_computation.window_weighted_num_samples,
          torch.tensor([[0.0]], dtype=torch.double, device=device),
      )
  
      # test RecMetricComputation._aggregate_window_state
      for i in range(4):
          model_output = gen_test_batch(128)
          model_output = {
              k: v.to(device) for k, v in model_output.items()
          }
          ne.update(
              predictions={"DefaultTask": model_output["prediction"]},
              labels={"DefaultTask": model_output["label"]},
              weights={"DefaultTask": model_output["weight"]},
          )
  
          if i < 3:
              ne_metric = ne.compute()
              name = DefaultTaskInfo.name
              torch.allclose(
                  ne_metric[f"ne-{name}|lifetime_ne"],
                  ne_metric[f"ne-{name}|window_ne"],
              )
              ne_metric = ne.local_compute()
              torch.allclose(
                  ne_metric[f"ne-{name}|local_lifetime_ne"],
                  ne_metric[f"ne-{name}|local_window_ne"],
              )
          else:
              self.assertEqual(
                  ne_computation.window_cross_entropy_sum.size(),
                  torch.Size([1]),
              )
              self.assertEqual(
                  len(
                      ne_computation._batch_window_buffers[
                          "window_cross_entropy_sum"
                      ].buffers
                  ),
                  3,
              )
  
file_path: torchrec/torchrec/metrics/tests/test_gpu.py
imports: import copy
  import unittest
  import torch
  from torchrec.metrics.auc import AUCMetric
  from torchrec.metrics.metric_module import generate_metric_module, RecMetricModule
  from torchrec.metrics.metrics_config import DefaultMetricsConfig, DefaultTaskInfo, RecMetricEnum
  from torchrec.metrics.ne import NEMetric
  from torchrec.metrics.test_utils import gen_test_batch
label_desc: Use image node_id 3 for calling the TestGPU obj's underlying member method code with example usage: obj.test_window_metric() without return types