code: def __new__(cls, **kwargs):
      model_num_param = kwargs.pop("model_num_param")
      norm_prod_model_param_frame_accuracy = kwargs.pop(
          "norm_prod_model_param_frame_accuracy"
      )
      self = super(NASMaskedSeq2SeqJointMetrics, cls).__new__(
          cls, **kwargs
      )
      self.model_num_param = model_num_param
      self.norm_prod_model_param_frame_accuracy = (
          norm_prod_model_param_frame_accuracy
      )
      return self
  
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 NASMaskedSeq2SeqJointMetrics obj's underlying member method code with example usage: obj.__new__(cls) and returns: self