class_docstr: The PharmKGFull dataset from [zheng2020]_.
  
  ---
  name: PharmKG
  citation:
      github: biomed-AI/PharmKG
      author: Zheng
      year: 2020
      link: https://doi.org/10.1093/bib/bbaa344
  single: true
  statistics:
      entities: 188296
      relations: 39
      triples: 1093236
      training: 874588
      testing: 109324
      validation: 109324
docstr: Initialize the PharmKG dataset from [zheng2020]_.
  
  :param random_state: An optional random state to make the training/testing/validation split reproducible.
  :param kwargs: keyword arguments passed to :class:`pykeen.datasets.base.UnpackedRemoteDataset`.
code: def __init__(
      self,
      random_state: TorchRandomHint = 0,
      **kwargs,
  ):
      """Initialize the PharmKG dataset from [zheng2020]_.
  
      :param random_state: An optional random state to make the training/testing/validation split reproducible.
      :param kwargs: keyword arguments passed to :class:`pykeen.datasets.base.UnpackedRemoteDataset`.
      """
      super().__init__(
          url=RAW_URL,
          random_state=random_state,
          read_csv_kwargs=dict(
              usecols=[
                  "Entity1_name",
                  "relationship_type",
                  "Entity2_name",
              ],
              sep=",",
          ),
          **kwargs,
      )
  
file_path: pykeen/src/pykeen/datasets/pharmkg.py
imports: import click
  from docdata import parse_docdata
  from more_click import verbose_option
  from .base import SingleTabbedDataset, UnpackedRemoteDataset
  from ..typing import TorchRandomHint
label_desc: Use image node_id 1 to create a new PharmKG object from inherited base classes: SingleTabbedDataset with example: obj = PharmKG(random_state)