code: def batch_context(self, raw_batch, batch):
      context = super().batch_context(raw_batch, batch)
      context[DatasetFieldName.TOKENS] = [
          [
              token.value
              for token in self.tokenizer.tokenize(
                  row[self.text_column_name]
              )
          ]
          for row in raw_batch
      ]
      context[BatchContext.INDEX] = [1]
      context[self.text_column_name] = [
          row[self.text_column_name] for row in raw_batch
      ]
  
      return context
  
imports: from typing import Dict, List, Set, Union
  from pytext.common.constants import BatchContext, DatasetFieldName, Stage
  from pytext.data import CommonMetadata
  from pytext.data.data_structures.annotation import Intent, REDUCE, SHIFT, Slot, Token, Tree, TreeBuilder
  from pytext.data.tensorizers import Tensorizer
  from pytext.data.tokenizers import Tokenizer
  from pytext.metrics.intent_slot_metrics import compute_all_metrics, FramePredictionPair, Node, Span
  from .channel import Channel, ConsoleChannel, FileChannel
  from .metric_reporter import MetricReporter
label_desc: Use image node_id 10 for calling the CompositionalMetricReporter obj's underlying member method code with example usage: obj.batch_context(raw_batch, batch) and returns: context