class_docstr: TFMA benchmark.
class_docstr_tok: ["TFMA","benchmark","."]
code: def _max_num_examples(self):
      # TFMA is slower than TFT, so use a smaller number of examples from the
      # dataset.
      limit = 100000
      parent_max = super()._max_num_examples()
      if parent_max is None:
          return limit
      return min(parent_max, limit)
  
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 3 for calling the TFMAV2BenchmarkBase obj's underlying member method code with example usage: obj._max_num_examples() and returns: min, limit