class_docstr: TFMA benchmark.
class_docstr_tok: ["TFMA","benchmark","."]
code: def benchmarkMetricsPlotsAndValidationsEvaluatorAUC10kMultiModel(
      self,
  ):
      self._runMetricsPlotsAndValidationsEvaluatorManualActuation(
          with_confidence_intervals=False,
          multi_model=True,
          metrics_specs=metric_specs_util.specs_from_metrics(
              [
                  tf.keras.metrics.AUC(
                      name="auc", num_thresholds=10000
                  ),
              ],
              model_names=["candidate", "baseline"],
          ),
          validation=True,
      )
  
imports: import copy
  import time
  import apache_beam
  import numpy
  import tensorflow
  import tensorflow_model_analysis
  from tensorflow_model_analysis.evaluators import metrics_plots_and_validations_evaluator
  from tensorflow_model_analysis.evaluators import poisson_bootstrap
  from tensorflow_model_analysis.extractors import example_weights_extractor
  from tensorflow_model_analysis.extractors import features_extractor
  from tensorflow_model_analysis.extractors import labels_extractor
  from tensorflow_model_analysis.extractors import legacy_input_extractor
  from tensorflow_model_analysis.extractors import predictions_extractor
  from tensorflow_model_analysis.extractors import unbatch_extractor
  import tfx
  from tfx.benchmarks import benchmark_utils
  from tfx.benchmarks import benchmark_base
  from tfx_bsl.coders import example_coder
  from tfx_bsl.tfxio import record_based_tfxio
  from tfx_bsl.tfxio import test_util
label_desc: Use image node_id 27 for calling the TFMAV2BenchmarkBase obj's underlying member method code with example usage: obj.benchmarkMetricsPlotsAndValidationsEvaluatorAUC10kMultiModel() without return types