code: def test_input_format_for_diabetes(queue):
      diabetes = datasets.load_diabetes()
  
      c_contiguous_numpy = np.asanyarray(
          diabetes.data, dtype="float", order="C"
      )
      assert c_contiguous_numpy.flags.c_contiguous
      assert not c_contiguous_numpy.flags.f_contiguous
      assert not c_contiguous_numpy.flags.fnc
  
      clf = SVR(kernel="linear", C=10.0)
      clf.fit(c_contiguous_numpy, diabetes.target, queue=queue)
      dual_c_contiguous_numpy = clf.dual_coef_
      res_c_contiguous_numpy = clf.predict(
          c_contiguous_numpy, queue=queue
      )
  
      f_contiguous_numpy = np.asanyarray(
          diabetes.data, dtype="float", order="F"
      )
      assert not f_contiguous_numpy.flags.c_contiguous
      assert f_contiguous_numpy.flags.f_contiguous
      assert f_contiguous_numpy.flags.fnc
  
      clf = SVR(kernel="linear", C=10.0)
      clf.fit(f_contiguous_numpy, diabetes.target, queue=queue)
      dual_f_contiguous_numpy = clf.dual_coef_
      res_f_contiguous_numpy = clf.predict(
          f_contiguous_numpy, queue=queue
      )
      assert_allclose(dual_c_contiguous_numpy, dual_f_contiguous_numpy)
      assert_allclose(res_c_contiguous_numpy, res_f_contiguous_numpy)
  
imports: import numpy
  import pytest
  import sklearn.utils.estimator_checks
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from sklearn import datasets
  from sklearn.metrics.pairwise import rbf_kernel
  from sklearn.svm import SVR
  from sklearn.utils.estimator_checks import check_estimator
  from onedal.svm import SVR
  from onedal.tests.utils._device_selection import get_queues, pass_if_not_implemented_for_gpu
label_desc: Use image node_id 6 for calling a global function with example usage: test_input_format_for_diabetes(queue) without return types