class_docstr: Contains transductive train and inductive inference/validation/test datasets.
class_docstr_tok: ["Contains","transductive","train","and","inductive","inference\/validation\/test","datasets","."]
docstr: Make a summary string of all of the factories.
docstr_tok: ["Make","a","summary","string","of","all","of","the","factories","."]
code: def summary_str(
      self,
      title: Optional[str] = None,
      show_examples: Optional[int] = 5,
      end="\n",
  ) -> str:
      """Make a summary string of all of the factories."""
      rows = self._summary_rows()
      n_triples = sum(count for *_, count in rows)
      rows.append(("Total", "-", "-", n_triples))
      t = tabulate(
          rows, headers=["Name", "Entities", "Relations", "Triples"]
      )
      rv = f"{title or self.__class__.__name__} (create_inverse_triples={self.create_inverse_triples})\n{t}"
      if show_examples:
          if not isinstance(self.transductive_training, TriplesFactory):
              raise AttributeError(
                  f"{self.transductive_training.__class__} does not have labeling information."
              )
          examples = tabulate(
              self.transductive_training.label_triples(
                  self.transductive_training.mapped_triples[
                      :show_examples
                  ]
              ),
              headers=["Head", "Relation", "tail"],
          )
          rv += "\n" + examples
      return rv + end
  
imports: from __future__ import annotations
  import logging
  import pathlib
  from dataclasses import dataclass
  from typing import Any, Iterable, Mapping, Optional, Union
  from pystow.utils import download, name_from_url
  from tabulate import tabulate
  from ...constants import PYKEEN_DATASETS
  from ...triples import CoreTriplesFactory, TriplesFactory
  from ...utils import normalize_path
label_desc: Use image node_id 2 for calling the InductiveDataset obj's underlying member method code with example usage: obj.summary_str(title, show_examples, end) and returns: unknown