code: def compute_accuracy_sum(
      labels: torch.Tensor,
      predictions: torch.Tensor,
      weights: torch.Tensor,
      threshold: float = 0.5,
  ) -> torch.Tensor:
      predictions = predictions.double()
      return torch.sum(
          weights * ((predictions >= threshold) == labels), dim=-1
      )
  
file_path: torchrec/torchrec/metrics/accuracy.py
imports: from typing import Any, cast, Dict, List, Optional, Type
  import torch
  from torchrec.metrics.metrics_namespace import MetricName, MetricNamespace, MetricPrefix
  from torchrec.metrics.rec_metric import MetricComputationReport, RecMetric, RecMetricComputation, RecMetricException
label_desc: Use image node_id 2 for calling a global function with example usage: compute_accuracy_sum(labels, predictions, weights, threshold) and returns: torch