code: 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,
      )
  
file_path: clearml/examples/frameworks/tensorflow/legacy/tensorboard_pr_curve.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os.path
  from tempfile import gettempdir
  from absl import app
  from absl import flags
  from six.moves import xrange
  import tensorflow
  from tensorboard.plugins.pr_curve import summary
  from clearml import Task
label_desc: Use image node_id 2 for calling a global function with example usage: run_all(logdir, steps, thresholds, verbose) without return types