code: def gen_content(self, metrics, loss, preds, targets, scores, context):
      for i, row in enumerate(
          super().gen_content(
              metrics, loss, preds, targets, scores, context
          )
      ):
          topk_raw_preds = [
              self.tensorizers["trg_seq_tokens"].stringify(pred).upper()
              for pred in context["topk_tree_predictions"][i]
          ]
          topk_preds = [
              self.validated_annotation(pred) for pred in topk_raw_preds
          ]
          samplewise_losses = [
              (
                  context["losses"][loss_name][i]
                  if (
                      "losses" in context
                      and loss_name in context["losses"]
                  )
                  else None
              )
              for loss_name in MaskedCompositionalSeq2SeqFileChannel.SAMPLEWISE_LOSSES
          ]
          row.extend(
              [
                  context["predicted_length"][i],
                  context["target_length"][i],
                  topk_preds,
                  topk_raw_preds,
                  # scores is assumed to be in descending order
                  #    so we individually log the highest score to sort the output file later
                  scores[i][0],
                  scores[i],
              ]
              + samplewise_losses
          )
  
          yield row
  
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 2 for calling the MaskedCompositionalSeq2SeqFileChannel obj's underlying member method code with example usage: obj.gen_content(metrics, loss, preds, targets, scores, context) without return types