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https://github.com/saymrwulf/pytorch.git
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8286ce1e3a
Summary: Closes https://github.com/caffe2/caffe2/pull/1260 Differential Revision: D5906739 Pulled By: Yangqing fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
51 lines
2 KiB
Python
51 lines
2 KiB
Python
# Copyright (c) 2016-present, Facebook, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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##############################################################################
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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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**hu.gcs)
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def test_channel_shuffle(self, channels_per_group, groups, n, 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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op = core.CreateOperator("ChannelShuffle", ["X"], ["Y"],
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group=groups, kernel=1)
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def channel_shuffle_ref(X):
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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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return (Y_trns.reshape(X.shape),)
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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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