code: def from_config_and_label_names(cls, config, label_names: List[str]):
      cls.assert_metric_and_label_details(config, label_names)
  
      return cls(
          label_names,
          [
              ConsoleChannel(),
              FileChannel((Stage.TEST,), config.output_path),
          ],
          config.model_select_metric,
          config.target_label,
          config.text_column_names,
          config.additional_column_names,
          config.recall_at_precision_thresholds,
          config.is_memory_efficient,
          config.topk,
      )
  
imports: from enum import Enum
  from itertools import tee, zip_longest
  from typing import Generator, List, Optional, Sequence
  import torch
  from pytext.common.constants import Stage
  from pytext.data import CommonMetadata
  from pytext.metrics import ClassificationMetrics, compute_classification_metrics, compute_multi_label_classification_metrics, LabelListPrediction, LabelPrediction, LabelTopKPrediction, RECALL_AT_PRECISION_THRESHOLDS, safe_division
  from pytext.metrics.intent_slot_metrics import PerLabelConfusions
  from .channel import Channel, ConsoleChannel, FileChannel
  from .metric_reporter import MetricReporter
label_desc: Use image node_id 4 for calling the TopKClassificationMetricReporter obj's underlying member method code with example usage: obj.from_config_and_label_names(cls, config, label_names) and returns: cls