code: def calculate_metric(self):
      all_metrics = compute_nas_masked_metrics(
          self.create_frame_prediction_pairs(
              self.all_pred_trees, self.all_target_trees
          ),
          self.all_target_lens,
          self.all_target_length_preds,
          self.select_length_beam,
          overall_metrics=True,
          calculated_loss=self.calculate_loss(),
          all_predicted_frames=self.all_beam_preds,
          non_invalid_frame_pairs=self.create_frame_prediction_pairs(
              self.all_top_non_invalid, self.all_target_trees
          ),
          extracted_frame_pairs=self.create_frame_prediction_pairs(
              self.all_top_extract, self.all_target_trees
          ),
          model_num_param=self.total_param_count,
          ref_model_num_param=self.ref_model_num_param,
          ref_frame_accuracy=self.ref_frame_accuracy,
          param_importance=self.param_importance,
      )
      return all_metrics
  
imports: from collections import defaultdict
  from typing import Dict, List
  import numpy
  from pytext.common.constants import Stage
  from pytext.data.tensorizers import Tensorizer
  from pytext.metric_reporters.channel import ConsoleChannel
  from pytext.metric_reporters.compositional_metric_reporter import CompositionalMetricReporter
  from pytext.metric_reporters.seq2seq_compositional import CompositionalSeq2SeqFileChannel, Seq2SeqCompositionalMetricReporter
  from pytext.metrics.intent_slot_metrics import FramePredictionPair
  from pytext.metrics.mask_metrics import compute_masked_metrics, compute_nas_masked_metrics
  from .compositional_utils import extract_beam_subtrees, filter_invalid_beams
label_desc: Use image node_id 4 for calling the NASMaskedSeq2SeqCompositionalMetricReporter obj's underlying member method code with example usage: obj.calculate_metric() and returns: all_metrics