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49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import numpy as np
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import caffe2.python.hypothesis_test_util as hu
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from caffe2.python import core
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from hypothesis import given
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import hypothesis.strategies as st
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class ChannelShuffleOpsTest(hu.HypothesisTestCase):
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@given(
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channels_per_group=st.integers(min_value=1, max_value=5),
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groups=st.integers(min_value=1, max_value=5),
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n=st.integers(min_value=1, max_value=2),
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order=st.sampled_from(["NCHW", "NHWC"]),
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**hu.gcs)
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def test_channel_shuffle(self, channels_per_group, groups, n, order, gc, dc):
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X = np.random.randn(
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n, channels_per_group * groups, 5, 6).astype(np.float32)
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if order == "NHWC":
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# NCHW -> NHWC
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X = X.transpose((0, 2, 3, 1))
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op = core.CreateOperator("ChannelShuffle", ["X"], ["Y"],
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group=groups, kernel=1, order=order,
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device_option=gc)
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def channel_shuffle_ref(X):
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if order == "NHWC":
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# NHWC -> NCHW
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X = X.transpose((0, 3, 1, 2))
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Y_r = X.reshape(X.shape[0],
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groups,
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X.shape[1] // groups,
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X.shape[2],
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X.shape[3])
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Y_trns = Y_r.transpose((0, 2, 1, 3, 4))
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Y_reshaped = Y_trns.reshape(X.shape)
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if order == "NHWC":
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# NCHW -> NHWC
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Y_reshaped = Y_reshaped.transpose((0, 2, 3, 1))
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return (Y_reshaped,)
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self.assertReferenceChecks(gc, op, [X], channel_shuffle_ref)
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self.assertGradientChecks(gc, op, [X], 0, [0])
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self.assertDeviceChecks(dc, op, [X], [0])
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