class_docstr: An abstract class for specifying padding values.
class_docstr_tok: ["An","abstract","class","for","specifying","padding","values","."]
code: def get_value(
      self,
      store_type: Optional[Union[NodeType, EdgeType]] = None,
      attr_name: Optional[str] = None,
  ) -> Union[int, float]:
      pass
  
imports: from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import torch
  import torch.nn.functional
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.data.datapipes import functional_transform
  from torch_geometric.data.storage import EdgeStorage, NodeStorage
  from torch_geometric.transforms import BaseTransform
  from torch_geometric.typing import EdgeType, NodeType
label_desc: Use image node_id 1 for calling the Padding obj's underlying member method code with example usage: obj.get_value(store_type, attr_name) without return types