code: def __init__(
      self, keys: List[Union[NodeType, EdgeType]], out_channels: int
  ):
      super().__init__()
      self.out_channels = out_channels
      self.lins = torch.nn.ModuleDict()
      for key in keys:
          self.lins[key2str(key)] = Linear(-1, out_channels, bias=False)
  
imports: import copy
  import warnings
  from typing import Any, Dict, List, Optional, Union
  import torch
  from torch import Tensor
  from torch.nn import Module, Parameter
  from torch_geometric.nn.conv import MessagePassing
  from torch_geometric.nn.dense import Linear
  from torch_geometric.nn.fx import Transformer
  from torch_geometric.typing import EdgeType, Metadata, NodeType, SparseTensor
  from torch_geometric.utils.hetero import get_unused_node_types
label_desc: Use image node_id 1 to create a new LinearAlign object from inherited base classes: torch.nn with example: obj = LinearAlign(keys, out_channels)