class_docstr: A plain python object modeling a single graph with various
  (optional) attributes:
  
  Args:
      x (Tensor, optional): Node feature matrix with shape :obj:`[num_nodes,
          num_node_features]`. (default: :obj:`None`)
      edge_index (LongTensor, optional): Graph connectivity in COO format
          with shape :obj:`[2, num_edges]`. (default: :obj:`None`)
      edge_attr (Tensor, optional): Edge feature matrix with shape
          :obj:`[num_edges, num_edge_features]`. (default: :obj:`None`)
      y (Tensor, optional): Graph or node targets with arbitrary shape.
          (default: :obj:`None`)
      pos (Tensor, optional): Node position matrix with shape
          :obj:`[num_nodes, num_dimensions]`. (default: :obj:`None`)
  
  The data object is not restricted to these attributes and can be extented
  by any other additional data.
docstr: Returns all names of graph attributes.
docstr_tok: ["Returns","all","names","of","graph","attributes","."]
code: def keys(self):
      r"""Returns all names of graph attributes."""
      keys = [
          key for key in self.__dict__.keys() if self[key] is not None
      ]
      keys = [
          key for key in keys if key[:2] != "__" and key[-2:] != "__"
      ]
      return keys
  
imports: import re
  import torch
label_desc: Use image node_id 5 for calling the Data obj's underlying member method code with example usage: obj.keys() and returns: keys