code: def __init__(
      self,
      channels,
      log_gradient,
      tensorizers,
      accept_flat_intents_slots,
      model_select_metric_key,
      select_length_beam,
      print_length_metrics,
  ):
      super().__init__(
          channels, log_gradient, tensorizers, accept_flat_intents_slots
      )
      self.model_select_metric_key = model_select_metric_key
      if model_select_metric_key == "fa":
          self.lower_is_better = False
      else:
          self.lower_is_better = True
      self.select_length_beam = select_length_beam
      self.print_length_metrics = print_length_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 1 to create a new MaskedSeq2SeqCompositionalMetricReporter object from inherited base classes: Seq2SeqCompositionalMetricReporter with example: obj = MaskedSeq2SeqCompositionalMetricReporter(channels, log_gradient, tensorizers, accept_flat_intents_slots, model_select_metric_key, select_length_beam, print_length_metrics)