class_docstr: TFMA benchmark.
class_docstr_tok: ["TFMA","benchmark","."]
code: def __init__(self, dataset, **kwargs):
      # Benchmark runners may pass extraneous arguments we don't care about.
      del kwargs
      super().__init__()
      self._dataset = dataset
  
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 1 to create a new TFMAV2BenchmarkBase object from inherited base classes: benchmark_base with example: obj = TFMAV2BenchmarkBase(dataset)