class_docstr: The Myket Android Application Install dataset from the
  `"Effect of Choosing Loss Function when Using T-Batching for Representation
  Learning on Dynamic Networks" <https://arxiv.org/abs/2308.06862>`_ paper.
  The dataset contains a temporal graph of application install interactions
  in an Android application market.
  
  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`)
      force_reload (bool, optional): Whether to re-process the dataset.
          (default: :obj:`False`)
  
  **STATS:**
  
  .. list-table::
      :widths: 10 10 10 10 10
      :header-rows: 1
  
      * - Name
        - #nodes
        - #edges
        - #features
        - #classes
      * - Myket
        - 17,988
        - 694,121
        - 33
        - 1
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code: def download(self) -> None:
      for file_name in self.raw_file_names:
          download_url(f"{self.url}/{file_name}", self.raw_dir)
  
file_path: pytorch_geometric/torch_geometric/datasets/myket.py
imports: from typing import Callable, List, Optional
  import numpy
  import torch
  from torch_geometric.data import InMemoryDataset, TemporalData, download_url
label_desc: Use image node_id 4 for calling the MyketDataset obj's underlying member method code with example usage: obj.download() without return types