code: def _compute(self) -> List[MetricComputationReport]:
      return [
          MetricComputationReport(
              name=MetricName.MULTICLASS_RECALL,
              metric_prefix=MetricPrefix.LIFETIME,
              value=compute_multiclass_recall_at_k(
                  cast(torch.Tensor, self.tp_at_k),
                  cast(torch.Tensor, self.total_weights),
              ),
          ),
          MetricComputationReport(
              name=MetricName.MULTICLASS_RECALL,
              metric_prefix=MetricPrefix.WINDOW,
              value=compute_multiclass_recall_at_k(
                  self.get_window_state("tp_at_k"),
                  self.get_window_state("total_weights"),
              ),
          ),
      ]
  
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 the MulticlassRecallMetricComputation obj's underlying member method code with example usage: obj._compute() and returns: list