code: def test_pointwise():
      interactions = movielens.get_movielens_dataset("100K")
  
      train, test = random_train_test_split(
          interactions, random_state=RANDOM_STATE
      )
  
      model = ImplicitFactorizationModel(
          loss="pointwise",
          n_iter=10,
          batch_size=1024,
          learning_rate=1e-2,
          l2=1e-6,
          use_cuda=CUDA,
      )
      model.fit(train)
  
      mrr = mrr_score(model, test, train=train).mean()
  
      assert mrr + EPSILON > 0.05
  
file_path: spotlight/tests/factorization/test_implicit.py
imports: import os
  import numpy
  import pytest
  import torch
  from spotlight.cross_validation import random_train_test_split
  from spotlight.datasets import movielens
  from spotlight.evaluation import mrr_score
  from spotlight.factorization.implicit import ImplicitFactorizationModel
  from spotlight.factorization.representations import BilinearNet
  from spotlight.layers import BloomEmbedding
label_desc: Use image node_id 1 for calling a global function with example usage: test_pointwise() without return types