text: import sys
  import timeit
  import numpy as np
  import os.path as osp
  
  sys.path.insert(0, osp.dirname(osp.abspath(__file__)) + '/../../..')
  
  from fastreid.evaluation.rank import evaluate_rank
  from fastreid.evaluation.roc import evaluate_roc
  
  """
  Test the speed of cython-based evaluation code. The speed improvements
  can be much bigger when using the real reid data, which contains a larger
  amount of query and gallery images.
  Note: you might encounter the following error:
    'AssertionError: Error: all query identities do not appear in gallery'.
  This is normal because the inputs are random numbers. Just try again.
  """
  
  print('*** Compare running time ***')
  
  setup = '''
  import sys
  import os.path as osp
  import numpy as np
  sys.path.insert(0, osp.dirname(osp.abspath(__file__)) + '/../../..')
  from fastreid.evaluation.rank import evaluate_rank
  from fastreid.evaluation.roc import evaluate_roc
  num_q = 30
  num_g = 300
  dim = 512
  max_rank = 5
  q_feats = np.random.rand(num_q, dim).astype(np.float32) * 20
  q_feats = q_feats / np.linalg.norm(q_feats, ord=2, axis=1, keepdims=True)
  g_feats = np.random.rand(num_g, dim).astype(np.float32) * 20
  g_feats = g_feats / np.linalg.norm(g_feats, ord=2, axis=1, keepdims=True)
  distmat = 1 - np.dot(q_feats, g_feats.transpose())
  q_pids = np.random.randint(0, num_q, size=num_q)
  g_pids = np.random.randint(0, num_g, size=num_g)
  q_camids = np.random.randint(0, 5, size=num_q)
  g_camids = np.random.randint(0, 5, size=num_g)
  '''
  
  print('=> Using CMC metric')
  pytime = timeit.timeit(
      'evaluate_rank(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_cython=False)',
      setup=setup,
      number=20
  )
  cytime = timeit.timeit(
      'evaluate_rank(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_cython=True)',
      setup=setup,
      number=20
  )
  print('Python time: {} s'.format(pytime))
  print('Cython time: {} s'.format(cytime))
  print('CMC Cython is {} times faster than python\n'.format(pytime / cytime))
  
  print('=> Using ROC metric')
  pytime = timeit.timeit(
      'evaluate_roc(distmat, q_pids, g_pids, q_camids, g_camids, use_cython=False)',
      setup=setup,
      number=20
  )
  cytime = timeit.timeit(
      'evaluate_roc(distmat, q_pids, g_pids, q_camids, g_camids, use_cython=True)',
      setup=setup,
      number=20
  )
  print('Python time: {} s'.format(pytime))
  print('Cython time: {} s'.format(cytime))
  print('ROC Cython is {} times faster than python\n'.format(pytime / cytime))
  
  print("=> Check precision")
  num_q = 30
  num_g = 300
  dim = 512
  max_rank = 5
  q_feats = np.random.rand(num_q, dim).astype(np.float32) * 20
  q_feats = q_feats / np.linalg.norm(q_feats, ord=2, axis=1, keepdims=True)
  g_feats = np.random.rand(num_g, dim).astype(np.float32) * 20
  g_feats = g_feats / np.linalg.norm(g_feats, ord=2, axis=1, keepdims=True)
  distmat = 1 - np.dot(q_feats, g_feats.transpose())
  q_pids = np.random.randint(0, num_q, size=num_q)
  g_pids = np.random.randint(0, num_g, size=num_g)
  q_camids = np.random.randint(0, 5, size=num_q)
  g_camids = np.random.randint(0, 5, size=num_g)
  
  cmc_py, mAP_py, mINP_py = evaluate_rank(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_cython=False)
  
  cmc_cy, mAP_cy, mINP_cy = evaluate_rank(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_cython=True)
  
  np.testing.assert_allclose(cmc_py, cmc_cy, rtol=1e-3, atol=1e-6)
  np.testing.assert_allclose(mAP_py, mAP_cy, rtol=1e-3, atol=1e-6)
  np.testing.assert_allclose(mINP_py, mINP_cy, rtol=1e-3, atol=1e-6)
  print('Rank results between python and cython are the same!')
  
  scores_cy, labels_cy = evaluate_roc(distmat, q_pids, g_pids, q_camids, g_camids, use_cython=True)
  scores_py, labels_py = evaluate_roc(distmat, q_pids, g_pids, q_camids, g_camids, use_cython=False)
  
  np.testing.assert_allclose(scores_cy, scores_py, rtol=1e-3, atol=1e-6)
  np.testing.assert_allclose(labels_cy, labels_py, rtol=1e-3, atol=1e-6)
  print('ROC results between python and cython are the same!\n')
  
  print("=> Check exact values")
  print("mAP = {} \ncmc = {}\nmINP = {}\nScores = {}".format(np.array(mAP_cy), cmc_cy, np.array(mINP_cy), scores_cy))
  