code: def _get_states(
      labels: torch.Tensor,
      predictions: torch.Tensor,
      weights: torch.Tensor,
  ) -> Dict[str, torch.Tensor]:
      predictions = predictions.double()
      error_sum = torch.sum(weights * torch.abs(labels - predictions))
      return {
          "error_sum": error_sum,
          "weighted_num_samples": torch.sum(weights),
      }
  
file_path: torchrec/torchrec/metrics/tests/test_mae.py
imports: import unittest
  from typing import Dict, Type
  import torch
  from torchrec.metrics.mae import compute_mae, MAEMetric
  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 1 for calling the TestMAEMetric obj's underlying member method code with example usage: obj._get_states(labels, predictions, weights) and returns: dict