code: def __init__(
      self,
      channels: List[Channel],
      log_gradient: bool,
      tensorizers: Dict[str, Tensorizer],
      accept_flat_intents_slots: bool,
  ) -> None:
      super().__init__(channels, log_gradient, tensorizers)
      self.accept_flat_intents_slots = accept_flat_intents_slots
  
imports: from typing import Dict, List, Optional
  from pytext.common.constants import BatchContext, DatasetFieldName, RawExampleFieldName, Stage
  from pytext.data.data_structures.annotation import Annotation, INVALID_TREE_STR
  from pytext.data.tensorizers import Tensorizer
  from pytext.metric_reporters.channel import Channel, ConsoleChannel
  from pytext.metric_reporters.compositional_metric_reporter import CompositionalMetricReporter
  from pytext.metric_reporters.metric_reporter import MetricReporter
  from pytext.metric_reporters.seq2seq_metric_reporter import Seq2SeqFileChannel, Seq2SeqMetricReporter
  from pytext.metrics.intent_slot_metrics import compute_all_metrics, FramePredictionPair
label_desc: Use image node_id 1 to create a new Seq2SeqCompositionalMetricReporter object from inherited base classes: Seq2SeqMetricReporter with example: obj = Seq2SeqCompositionalMetricReporter(channels, log_gradient, tensorizers, accept_flat_intents_slots)