class_docstr: The breast cancer (BRCA TCGA Pan-Cancer Atlas) dataset consisting of
  patients with survival information and gene expression data from
  `cBioPortal <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4160307/>`_
  and a network of biological interactions between those nodes from
  `Pathway Commons <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145667/>`_.
  The dataset contains the gene features of 1,082 patients, and the overall
  survival time (in months) of each patient as label.
  
  Pre-processing and example model codes on how to use this dataset can be
  found `here <https://github.com/cannin/pyg_pathway_commons_cbioportal>`_.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      transform (callable, optional): A function/transform that takes in an
          :obj:`torch_geometric.data.Data` object and returns a transformed
          version. The data object will be transformed before every access.
          (default: :obj:`None`)
      pre_transform (callable, optional): A function/transform that takes in
          an :obj:`torch_geometric.data.Data` object and returns a
          transformed version. The data object will be transformed before
          being saved to disk. (default: :obj:`None`)
      pre_filter (callable, optional): A function that takes in an
          :obj:`torch_geometric.data.Data` object and returns a boolean
          value, indicating whether the data object should be included in the
          final dataset. (default: :obj:`None`)
      force_reload (bool, optional): Whether to re-process the dataset.
          (default: :obj:`False`)
  
  **STATS:**
  
  .. list-table::
      :widths: 10 10 10 10
      :header-rows: 1
  
      * - #graphs
        - #nodes
        - #edges
        - #features
      * - 1,082
        - 9,288
        - 271,771
        - 1,082
code: def download(self) -> None:
      path = download_url(self.url, self.root)
      extract_zip(path, self.root)
      os.unlink(path)
      fs.rm(self.raw_dir)
      os.rename(osp.join(self.root, "brca_tcga"), self.raw_dir)
  
file_path: pytorch_geometric/torch_geometric/datasets/brca_tgca.py
imports: import os
  import os.path
  from typing import Callable, List, Optional
  import numpy
  import torch
  from torch_geometric.data import Data, InMemoryDataset, download_url, extract_zip
  from torch_geometric.io import fs
label_desc: Use image node_id 4 for calling the BrcaTcga obj's underlying member method code with example usage: obj.download() without return types