class_docstr: This class implements the RecMetricComputation for Recall on session level.
  
  The constructor arguments are defined in RecMetricComputation.
  See the docstring of RecMetricComputation for more detail.
code: def get_recall_states(
      self,
      labels: torch.Tensor,
      predictions: torch.Tensor,
      weights: torch.Tensor,
      session: torch.Tensor,
  ) -> Dict[str, torch.Tensor]:
      predictions_ranked = ranking_within_session(predictions, session)
      predictions_labels = (predictions_ranked < self.top_threshold).to(
          torch.int32
      )
      if self.run_ranking_of_labels:
          labels_ranked = ranking_within_session(labels, session)
          labels = (labels_ranked < self.top_threshold).to(torch.int32)
      num_true_pos = _calc_num_true_pos(
          labels, predictions_labels, weights
      )
      num_false_neg = _calc_num_false_neg(
          labels, predictions_labels, weights
      )
  
      return {
          NUM_TRUE_POS: num_true_pos,
          NUM_FALSE_NEGATIVE: num_false_neg,
      }
  
imports: import logging
  from typing import Any, cast, Dict, List, Optional, Set, Type, Union
  import torch
  from torch import distributed
  from torchrec.metrics.metrics_config import RecTaskInfo, SessionMetricDef
  from torchrec.metrics.metrics_namespace import MetricName, MetricNamespace, MetricPrefix
  from torchrec.metrics.rec_metric import MetricComputationReport, RecComputeMode, RecMetric, RecMetricComputation, RecMetricException
label_desc: Use image node_id 4 for calling the RecallSessionMetricComputation obj's underlying member method code with example usage: obj.get_recall_states(labels, predictions, weights, session) and returns: dict