class_docstr: TFMA benchmark.
class_docstr_tok: ["TFMA","benchmark","."]
docstr: Read the raw dataset and massage examples into Extracts.
docstr_tok: ["Read","the","raw","dataset","and","massage","examples","into","Extracts","."]
code: def _readDatasetIntoExtracts(self):
      """Read the raw dataset and massage examples into Extracts."""
      records = []
      for x in self._dataset.read_raw_dataset(
          deserialize=False, limit=self._max_num_examples()
      ):
          records.append(
              {tfma.INPUT_KEY: x, tfma.SLICE_KEY_TYPES_KEY: ()}
          )
      return records
  
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 8 for calling the TFMAV2BenchmarkBase obj's underlying member method code with example usage: obj._readDatasetIntoExtracts() and returns: records