code: def compute_logloss(
      ce_sum: torch.Tensor,
      pos_labels: torch.Tensor,
      neg_labels: torch.Tensor,
      eta: float,
  ) -> torch.Tensor:
      labels_sum = pos_labels + neg_labels
      labels_sum.clamp_(min=eta)
      return ce_sum / labels_sum
  
file_path: torchrec/torchrec/metrics/ne.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 4 for calling a global function with example usage: compute_logloss(ce_sum, pos_labels, neg_labels, eta) and returns: unknown