code: def test_lightgcn_component_definition(deeprec_config_path):
      yaml_file = os.path.join(deeprec_config_path, "lightgcn.yaml")
  
      df = movielens.load_pandas_df(size="100k")
      train, test = python_stratified_split(df, ratio=0.75)
  
      data = ImplicitCF(train=train, test=test)
  
      hparams = prepare_hparams(yaml_file, embed_size=64)
      model = LightGCN(hparams, data)
  
      assert model.norm_adj is not None
      assert model.ua_embeddings.shape == [943, 64]
      assert model.ia_embeddings.shape == [1682, 64]
      assert model.u_g_embeddings is not None
      assert model.pos_i_g_embeddings is not None
      assert model.neg_i_g_embeddings is not None
      assert model.batch_ratings is not None
      assert model.loss is not None
      assert model.opt is not None
      assert model.batch_size == 1024
      assert model.epochs == 1000
  
file_path: recommenders/tests/unit/recommenders/models/test_deeprec_model.py
imports: import os
  import pytest
  from recommenders.datasets import movielens
  from recommenders.datasets.amazon_reviews import download_and_extract, data_preprocessing
  from recommenders.datasets.python_splitters import python_stratified_split
label_desc: Use image node_id 9 for calling a global function with example usage: test_lightgcn_component_definition(deeprec_config_path) without return types