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| 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 |
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| @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, deadline=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) |
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| self.assertDeviceChecks(dc, op, [X], [0]) |
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| if __name__ == "__main__": |
| import unittest |
| unittest.main() |
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