class_docstr: Base class for classes representing a dataset for the benchmark.
class_docstr_tok: ["Base","class","for","classes","representing","a","dataset","for","the","benchmark","."]
docstr: Generate the inference and tf.ModelAnalysis format SavedModels.
  
  This is usually done by running a Trainer on the raw dataset and exporting
  the inference and tf.ModelAnalysis format SavedModels.
  
  Args:
    args: String of extra arguments to use when generating the models.
docstr_tok: ["Generate","the","inference","and","tf.ModelAnalysis","format","SavedModels",".","This","is","usually","done","by","running","a","Trainer","on","the","raw","dataset","and","exporting","the","inference","and","tf.ModelAnalysis","format","SavedModels",".","Args",":","args",":","String","of","extra","arguments","to","use","when","generating","the","models","."]
code: def generate_models(self, args):
      """Generate the inference and tf.ModelAnalysis format SavedModels.
  
      This is usually done by running a Trainer on the raw dataset and exporting
      the inference and tf.ModelAnalysis format SavedModels.
  
      Args:
        args: String of extra arguments to use when generating the models.
      """
      raise NotImplementedError()
  
file_path: tfx/tfx/benchmarks/benchmark_dataset.py
imports: import os
  import tensorflow
label_desc: Use image node_id 11 for calling the BenchmarkDataset obj's underlying member method code with example usage: obj.generate_models(args) without return types