code: def test_lrq(self):
      X = [
          "1 |user A |movie 1",
          "2 |user B |movie 2",
          "3 |user C |movie 3",
          "4 |user D |movie 4",
          "5 |user E |movie 1",
      ]
      model = VW(
          convert_to_vw=False,
          lrq="um4",
          lrqdropout=True,
          loss_function="quantile",
      )
      assert getattr(model, "lrq") == "um4"
      assert getattr(model, "lrqdropout")
      model.fit(X)
      prediction = model.predict([" |user C |movie 1"])
      assert np.allclose(prediction, [3.0], atol=1)
  
imports: from collections import namedtuple
  import os
  import numpy
  from packaging import version
  import pandas
  import pytest
  from scipy.sparse import csr_matrix
  from sklearn import datasets, __version__
  from sklearn.model_selection import KFold
  from sklearn.utils.estimator_checks import check_estimator
  from vowpalwabbit.sklearn import VW, VWClassifier, VWRegressor, tovw, VWMultiClassifier, VWRegressor
label_desc: Use image node_id 11 for calling the TestVW obj's underlying member method code with example usage: obj.test_lrq() without return types