text: # Copyright 2020 D-Wave Systems Inc.
  #
  #    Licensed under the Apache License, Version 2.0 (the "License");
  #    you may not use this file except in compliance with the License.
  #    You may obtain a copy of the License at
  #
  #        http://www.apache.org/licenses/LICENSE-2.0
  #
  #    Unless required by applicable law or agreed to in writing, software
  #    distributed under the License is distributed on an "AS IS" BASIS,
  #    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  #    See the License for the specific language governing permissions and
  #    limitations under the License.
  
  import unittest
  
  import dimod
  from dimod.exceptions import SamplerUnknownArgWarning
  import numpy as np
  
  
  # This sampler is an extremely thin wrapper around the
  # Initialized.parse_initial_states method, so we rely on that testing for
  # the most part, just doing the standard sampler tests and a few
  # integration tests
  @dimod.testing.load_sampler_bqm_tests(dimod.IdentitySampler)
  class TestIdentitySampler(unittest.TestCase):
      def test_passthrough(self):
          samples = [[-1, +1], [+1, -1]]
  
          sampler = dimod.IdentitySampler()
          sampleset = sampler.sample_ising({}, {(0, 1): 1},
                                           initial_states=samples)
  
          np.testing.assert_array_equal(sampleset.samples()[:, [0, 1]], samples)
  
      def test_passthrough(self):
          samples = [[-1, +1], [+1, -1]]
  
          sampler = dimod.IdentitySampler()
          sampleset = sampler.sample_ising({}, {(0, 1): 1},
                                           initial_states=samples,
                                           initial_states_generator='tile',
                                           num_reads=10)
  
          self.assertEqual(len(sampleset), 10)
          np.testing.assert_array_equal(sampleset.samples()[:2, [0, 1]], samples)
  
      def test_kwargs(self):
          sampler = dimod.IdentitySampler()
          bqm = dimod.BinaryQuadraticModel({}, {}, 0.0, dimod.SPIN)
  
          with self.assertWarns(SamplerUnknownArgWarning):
              sampleset = sampler.sample(bqm, a=1, b=4)
  