code: def test_sgd_learning_rate_field(u1_ml100k, pkf):
      """Ensure the learning_rate field is taken into account."""
  
      bsl_options = {
          "method": "sgd",
          "n_epochs": 1,
          "learning_rate": 0.005,
      }
      algo = BaselineOnly(bsl_options=bsl_options)
      rmse_sgd_lr_005 = cross_validate(algo, u1_ml100k, ["rmse"], pkf)[
          "test_rmse"
      ]
  
      bsl_options = {
          "method": "sgd",
          "n_epochs": 1,
          "learning_rate": 0.00005,
      }
      algo = BaselineOnly(bsl_options=bsl_options)
      rmse_sgd_lr_00005 = cross_validate(
          algo, u1_ml100k, ["rmse"], pkf
      )["test_rmse"]
  
      assert rmse_sgd_lr_005 != rmse_sgd_lr_00005
  
file_path: Surprise/tests/test_bsl_options.py
imports: import pytest
  from surprise import BaselineOnly
  from surprise.model_selection import cross_validate
label_desc: Use image node_id 6 for calling a global function with example usage: test_sgd_learning_rate_field(u1_ml100k, pkf) without return types