code: def __init__(self, indim, outdim, config):
      super(CINComp, self).__init__()
      basedim = config["feature_num"]
      self.conv = nn.Conv1d(indim * basedim, outdim, 1)
  
imports: import torch
  from torch import nn
  from torch.nn.init import xavier_normal_
  from copy import deepcopy
  from recbole.model.init import xavier_normal_initialization
  from recbole.model.abstract_recommender import ContextRecommender
label_desc: Use image node_id 1 to create a new CINComp object from inherited base classes: nn with example: obj = CINComp(indim, outdim, config)