code: def __init__(self, emb_dim: int, dropout: float = 0.25):
      super().__init__()
  
      self.encoder = torch.nn.Sequential(
          BitwiseEmbedding(emb_dim),
          torch.nn.Linear(emb_dim, emb_dim),
          torch.nn.Dropout(),
          torch.nn.GELU(),
      )
  
      self.aggr = LCMAggregation(emb_dim, emb_dim, project=False)
  
      self.decoder = torch.nn.Sequential(
          torch.nn.Linear(emb_dim, emb_dim),
          torch.nn.Dropout(dropout),
          torch.nn.GELU(),
          torch.nn.Linear(emb_dim, args.num_bits),
      )
  
imports: import argparse
  import torch
  import torch.nn.functional
  from torch import Tensor
  from torch_geometric.data import Data, InMemoryDataset
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import LCMAggregation
  from torch_geometric.transforms import BaseTransform
label_desc: Use image node_id 1 to create a new LCM object from inherited base classes: torch.nn with example: obj = LCM(emb_dim, dropout)