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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.ideep_test_util as mu
@unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.")
class ChannelShuffleTest(hu.HypothesisTestCase):
@given(size=st.integers(8, 10),
input_channels=st.integers(1, 3),
batch_size=st.integers(1, 32),
group=st.integers(2, 4),
stride=st.integers(1, 3),
pad=st.integers(0, 3),
kernel=st.integers(3, 5),
**mu.gcs)
@settings(max_examples=10, deadline=None)
def test_channel_shuffle(self, size, input_channels, batch_size, group, stride, pad, kernel, gc, dc):
op = core.CreateOperator(
"ChannelShuffle",
["X"],
["Y"],
group=group,
stride=stride,
pad=pad,
kernel=kernel,
)
X = np.random.rand(
batch_size, input_channels * group, size, size).astype(np.float32) - 0.5
self.assertDeviceChecks(dc, op, [X], [0])
self.assertGradientChecks(gc, op, [X], 0, [0])
if __name__ == "__main__":
unittest.main()
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