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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def run_all(logdir, steps, thresholds, verbose=False):
 """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. """

  # 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)