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, 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)

        self.assertDeviceChecks(dc, op, [X], [0])


if __name__ == "__main__":
    import unittest
    unittest.main()