code: def gen_content(self, metrics, loss, preds, targets, scores, context):
      batch_size = len(targets)
  
      for i in range(batch_size):
          yield [
              context[BatchContext.INDEX][i],
              context[DatasetFieldName.RAW_SEQUENCE][i],
              self.tensorizers["trg_seq_tokens"]
              .stringify(preds[i][0])
              .upper(),
              self.validated_annotation(
                  self.tensorizers["trg_seq_tokens"]
                  .stringify(preds[i][0])
                  .upper()
              ),
              self.validated_annotation(
                  self.tensorizers["trg_seq_tokens"]
                  .stringify(targets[i])
                  .upper()
              ),
          ]
  
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 4 for calling the CompositionalSeq2SeqFileChannel obj's underlying member method code with example usage: obj.gen_content(metrics, loss, preds, targets, scores, context) without return types