class_docstr: A plain old python object modeling a batch of
  :class:`deepsnap.graph.Graph` objects as one big (disconnected) graph,
  with :class:`torch_geometric.data.Data` being the
  base class that all its methods can also be used here.
  In addition, graphs can be reconstructed via the assignment vector
  :obj:`batch`, which maps each node to its respective graph identifier.
  
  .. note::
  
      For more detailed use of :class:`deepsnap.batch.Batch`, see the `examples 
      <https://github.com/snap-stanford/deepsnap/tree/master/examples>`_ folder.
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code: def __init__(self, batch=None, **kwargs):
      super(Batch, self).__init__(**kwargs)
  
      self.batch = batch
      self.__data_class__ = Graph
      self.__slices__ = None
  
file_path: deepsnap/deepsnap/batch.py
imports: import torch
  from deepsnap.graph import Graph
  from deepsnap.hetero_graph import HeteroGraph
  from typing import Callable, Dict, List
label_desc: Use image node_id 1 to create a new Batch object from inherited base classes: Graph with example: obj = Batch(batch)