code: def _main(trials):
      import itertools as itt
  
      import numpy as np
      from tqdm import tqdm
  
      from pykeen.datasets import get_dataset
  
      n_comb = trials * (trials - 1) // 2
      click.echo(
          f"Number of combinations: {trials} n Choose 2 = {n_comb}"
      )
  
      for dataset_name in [
          "nations",
          "umls",
          "kinships",
          "codexsmall",
          "wn18",
      ]:
          reference_dataset = get_dataset(dataset=dataset_name)
          remixed_datasets = [
              reference_dataset.remix(random_state=random_state)
              for random_state in range(trials)
          ]
          similarities = [
              a.similarity(b)
              for a, b in tqdm(
                  itt.combinations(remixed_datasets, r=2),
                  total=n_comb,
                  desc=dataset_name,
              )
          ]
          click.echo(
              f"[{dataset_name}] Similarities Mean: {np.mean(similarities):.3f}"
          )
          click.echo(
              f"[{dataset_name}] Similarities Std.: {np.std(similarities):.3f}"
          )
          click.echo(
              f"[{dataset_name}] Relative Std.: {np.std(similarities) / np.mean(similarities):.3%}"
          )
  
imports: from typing import List, Sequence
  import click
  from .splitting import normalize_ratios, split
  from .triples_factory import CoreTriplesFactory, cat_triples
label_desc: Use image node_id 3 for calling a global function with example usage: _main(trials) without return types