code: def toy_test_data():
      x = np.array(
          [
              [1.0, 1.0],
              [40, 30],
              [50, 36],
          ]
      )
      rnd = np.random.RandomState(136)
      x += rnd.randn(*x.shape)
      return x
  
imports: import numpy
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  import pytest
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.preprocessing import scale
  from sksurv.column import encode_categorical
  from sksurv.datasets import load_gbsg2
  from sksurv.exceptions import NoComparablePairException
  from sksurv.svm._minlip import create_difference_matrix
  from sksurv.svm.minlip import HingeLossSurvivalSVM, MinlipSurvivalAnalysis
  from sksurv.testing import FixtureParameterFactory, assert_cindex_almost_equal
  from sksurv.util import Surv
label_desc: Use image node_id 3 for calling a global function with example usage: toy_test_data() and returns: x