code: def get_multiclass_recall_states(
      predictions: torch.Tensor,
      labels: torch.Tensor,
      weights: torch.Tensor,
      n_classes: int,
  ) -> Dict[str, torch.Tensor]:
      true_positives_at_k_sum = compute_true_positives_at_k(
          predictions, labels, weights, n_classes
      )
      return {
          "tp_at_k": true_positives_at_k_sum,
          "total_weights": torch.sum(weights, dim=-1),
      }
  
file_path: torchrec/torchrec/metrics/multiclass_recall.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 3 for calling a global function with example usage: get_multiclass_recall_states(predictions, labels, weights, n_classes) and returns: dict