mindspore/tests/st/nn/test_channel_shuffle.py

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2022-10-20 20:05:15 +08:00
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
import numpy as np
import pytest
import mindspore as ms
import mindspore.nn as nn
class Net(nn.Cell):
def __init__(self, groups):
super(Net, self).__init__()
self.channel_shuffle = nn.ChannelShuffle(groups)
def construct(self, x):
return self.channel_shuffle(x)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.platform_arm_cpu
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
def test_channel_shuffle_normal(mode):
"""
Feature: ChannelShuffle
Description: Verify the result of ChannelShuffle
Expectation: success
"""
ms.set_context(mode=mode)
net = Net(2)
x = ms.Tensor(np.arange(16).reshape((1, 4, 2, 2)), dtype=ms.int32)
out = net(x)
expect_out = np.array([[[[0, 1], [2, 3]], [[8, 9], [10, 11]],
[[4, 5], [6, 7]], [[12, 13], [14, 15]]]]).astype(np.int32)
assert np.allclose(out.asnumpy(), expect_out)