code: def run_all(logdir, steps, thresholds, verbose=False):
    
    # First, we generate data for a PR curve that assigns even weights for
    # predictions of all classes.
    run_name = 'colors'
    if verbose:
      print('--- Running: %s' % run_name)
    start_runs(
        logdir=logdir,
        steps=steps,
        run_name=run_name,
        thresholds=thresholds)
  
    # Next, we generate data for a PR curve that assigns arbitrary weights to
    # predictions.
    run_name = 'mask_every_other_prediction'
    if verbose:
      print('--- Running: %s' % run_name)
    start_runs(
        logdir=logdir,
        steps=steps,
        run_name=run_name,
        thresholds=thresholds,
        mask_every_other_prediction=True)
docs: Generate PR curve summaries.
  
    Arguments:
      logdir: The directory into which to store all the runs' data.
      steps: The number of steps to run for.
      verbose: Whether to print the names of runs into stdout during execution.
      thresholds: The number of thresholds to use for PR curves.