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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 LRNTest(hu.HypothesisTestCase):
@given(input_channels=st.integers(1, 3),
batch_size=st.integers(1, 3),
im_size=st.integers(1, 10),
order=st.sampled_from(["NCHW"]),
**mu.gcs)
@settings(deadline=10000)
def test_LRN(self, input_channels,
batch_size, im_size, order,
gc, dc):
op = core.CreateOperator(
"LRN",
["X"],
["Y", "Y_scale"],
size=5,
alpha=0.001,
beta=0.75,
bias=2.0,
order=order,
)
X = np.random.rand(
batch_size, input_channels, im_size, im_size).astype(np.float32)
self.assertDeviceChecks(dc, op, [X], [0])
self.assertGradientChecks(gc, op, [X], 0, [0])
if __name__ == "__main__":
unittest.main()
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