old_contents: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  
  import unittest
  import hypothesis.strategies as st
  from hypothesis import given, settings
  import numpy as np
  from caffe2.python import core, workspace
  import caffe2.python.hypothesis_test_util as hu
  import caffe2.python.mkl_test_util as mu
  
  
  @unittest.skipIf(not workspace.C.has_mkldnn,
                   "Skipping as we do not have mkldnn.")
  class MKLPoolTest(hu.HypothesisTestCase):
      @given(stride=st.integers(1, 3),
             pad=st.integers(0, 3),
             kernel=st.integers(3, 5),
             size=st.integers(7, 9),
             input_channels=st.integers(1, 3),
             batch_size=st.integers(1, 3),
             method=st.sampled_from(["MaxPool", "AveragePool"]),
             **mu.gcs)
      @settings(max_examples=2, timeout=100)
      def test_mkl_pooling(self, stride, pad, kernel, size,
                               input_channels, batch_size,
                               method, gc, dc):
          op = core.CreateOperator(
              method,
              ["X"],
              ["Y"],
              stride=stride,
              pad=pad,
              kernel=kernel,
          )
          X = np.random.rand(
              batch_size, input_channels, size, size).astype(np.float32)
  
          self.assertDeviceChecks(dc, op, [X], [0])
  
  
  if __name__ == "__main__":
      import unittest
      unittest.main()
  
new_contents: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  
  import unittest
  import hypothesis.strategies as st
  from hypothesis import given, settings, assume
  import numpy as np
  from caffe2.python import core, workspace
  import caffe2.python.hypothesis_test_util as hu
  import caffe2.python.mkl_test_util as mu
  
  
  @unittest.skipIf(not workspace.C.has_mkldnn,
                   "Skipping as we do not have mkldnn.")
  class MKLPoolTest(hu.HypothesisTestCase):
      @given(stride=st.integers(1, 3),
             pad=st.integers(0, 3),
             kernel=st.integers(3, 5),
             size=st.integers(7, 9),
             input_channels=st.integers(1, 3),
             batch_size=st.integers(1, 3),
             method=st.sampled_from(["MaxPool", "AveragePool"]),
             **mu.gcs)
      @settings(max_examples=2, timeout=100)
      def test_mkl_pooling(self, stride, pad, kernel, size,
                           input_channels, batch_size,
                           method, gc, dc):
          assume(pad < kernel)
          op = core.CreateOperator(
              method,
              ["X"],
              ["Y"],
              stride=stride,
              pad=pad,
              kernel=kernel,
          )
          X = np.random.rand(
              batch_size, input_channels, size, size).astype(np.float32)
  
          self.assertDeviceChecks(dc, op, [X], [0])
  
  
  if __name__ == "__main__":
      import unittest
      unittest.main()
  
subject: Fix MKL spatial pooling test