class_docstr: Computes recall for sets of labels and predictions.
  
  The metric deals with labels and predictions which are provided in the format
  of sets (stored as variable length numpy arrays). The recall is the
  micro averaged classification recall. The metric is suitable for the case
  where the number of classes is large or the list of classes could not be
  provided in advance.
  
  Example:
  Label: ['cats'],
  Predictions: {'classes': ['cats, dogs']}
  
  The recall is 1.
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code: def _default_name(self) -> str:
      return SET_MATCH_RECALL_NAME
  
file_path: model-analysis/tensorflow_model_analysis/metrics/set_match_confusion_matrix_metrics.py
imports: from typing import List, Optional, Union, Dict
  from tensorflow_model_analysis.metrics import confusion_matrix_metrics
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import preprocessors
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 2 for calling the SetMatchRecall obj's underlying member method code with example usage: obj._default_name() and returns: SET_MATCH_RECALL_NAME