class_docstr: Uniform padding independent of attribute name or node/edge type.
  
  Args:
      value (int or float, optional): The value to be used for padding.
          (default: :obj:`0.0`)
class_docstr_tok: ["Uniform","padding","independent","of","attribute","name","or","node\/edge","type",".","Args",":","value","(","int","or","float",",","optional",")",":","The","value","to","be","used","for","padding",".","(","default",":",":","obj",":","`","0.0","`",")"]
code: def __init__(self, value: Union[int, float] = 0.0):
      self.value = value
  
      if not isinstance(self.value, (int, float)):
          raise ValueError(
              f"Expected 'value' to be an integer or float "
              f"(got '{type(value)}'"
          )
  
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 to create a new UniformPadding object from inherited base classes: Padding with example: obj = UniformPadding(value)