code: def print_metrics(self) -> None:
      if self.size_32bit_model:
          print(f"\n\nsize of 32bit model = {self.size_32bit_model} MB")
      if self.size_8bit_model:
          print(f"\n\nsize of 8bit model = {self.size_8bit_model} MB")
      if self.size_4bit_model:
          print(f"\n\nsize of 4bit model = {self.size_4bit_model} MB")
      if self.current_model_parameter_size:
          print(
              f"\n\nparameter size of current model = {self.current_model_parameter_size} MB"
          )
      if self.frame_accuracy:
          print(f"\n\nFrame accuracy = {self.frame_accuracy * 100:.2f}")
      if self.frame_accuracy_top_k:
          print(
              f"\n\nTop k frame accuracy = {self.frame_accuracy_top_k * 100:.2f}"
          )
      if self.bracket_metrics:
          print("\n\nBracket Metrics")
          self.bracket_metrics.print_metrics()
      if self.tree_metrics:
          print("\n\nTree Metrics")
          self.tree_metrics.print_metrics()
      if self.length_metrics:
          print("\n\nLength Metrics :", self.length_metrics)
          print(
              f"Length Accuracy: {self.length_reports.accuracy * 100:.2f}"
          )
      if self.length_reports and self.print_length_metrics:
          print(
              "\n\nLength Reports :",
              self.length_reports.print_metrics(),
          )
      if self.non_invalid_fa:
          print(f"Non Invalid FA {self.non_invalid_fa}")
      if self.extracted_fa:
          print(f"Extracted FA {self.extracted_fa}")
      if self.percent_invalid_trees is not None:
          print(
              f"\n\n% Invalid Trees = {self.percent_invalid_trees * 100:.2f}%"
          )
      if self.percent_trees_wrong_label is not None:
          print(
              f"\n\n% Trees w/ wrong IN/SL = {self.percent_trees_wrong_label * 100:.2f}%"
          )
  
file_path: pytext/pytext/metrics/mask_metrics.py
imports: from typing import Dict, List, NamedTuple, Optional, Sequence
  from pytext.metrics import ClassificationMetrics, compute_classification_metrics, LabelPrediction
  from pytext.metrics.intent_slot_metrics import compute_all_metrics, compute_frame_accuracy, FrameAccuraciesByDepth, FramePredictionPair, IntentSlotMetrics, Node
  from sklearn.metrics import accuracy_score
label_desc: Use image node_id 1 for calling the MaskedSeq2SeqJointMetrics obj's underlying member method code with example usage: obj.print_metrics() without return types