forked from mindspore-Ecosystem/mindspore
116 lines
3.4 KiB
Python
116 lines
3.4 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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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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import numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore.ops import operations as P
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class ReverseV2Net(nn.Cell):
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def __init__(self, axis):
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super(ReverseV2Net, self).__init__()
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self.reverse_v2 = P.ReverseV2(axis)
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def construct(self, x):
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return self.reverse_v2(x)
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def reverse_v2(x_numpy, axis):
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x = Tensor(x_numpy)
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reverse_v2_net = ReverseV2Net(axis)
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output = reverse_v2_net(x).asnumpy()
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expected_output = np.flip(x_numpy, axis)
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np.testing.assert_array_equal(output, expected_output)
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def reverse_v2_3d(nptype):
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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x_numpy = np.arange(60).reshape(3, 4, 5).astype(nptype)
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reverse_v2(x_numpy, (0,))
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reverse_v2(x_numpy, (1,))
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reverse_v2(x_numpy, (2,))
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reverse_v2(x_numpy, (2, -2))
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reverse_v2(x_numpy, (-3, 1, 2))
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def reverse_v2_1d(nptype):
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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x_numpy = np.arange(4).astype(nptype)
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reverse_v2(x_numpy, (0,))
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reverse_v2(x_numpy, (-1,))
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_reverse_v2_float16():
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reverse_v2_1d(np.float16)
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reverse_v2_3d(np.float16)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_reverse_v2_float32():
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reverse_v2_1d(np.float32)
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reverse_v2_3d(np.float32)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_reverse_v2_uint8():
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reverse_v2_1d(np.uint8)
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reverse_v2_3d(np.uint8)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_reverse_v2_int16():
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reverse_v2_1d(np.int16)
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reverse_v2_3d(np.int16)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_reverse_v2_int32():
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reverse_v2_1d(np.int32)
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reverse_v2_3d(np.int32)
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_reverse_v2_int64():
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reverse_v2_1d(np.int64)
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reverse_v2_3d(np.int64)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_reverse_v2_invalid_axis():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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x = Tensor(np.arange(60).reshape(1, 2, 3, 2, 5).astype(np.int32))
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with pytest.raises(ValueError) as info:
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reverse_v2_net = ReverseV2Net((0, 1, 2, 1))
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_ = reverse_v2_net(x)
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assert "'axis' cannot contain duplicate dimensions" in str(info.value)
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with pytest.raises(ValueError) as info:
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reverse_v2_net = ReverseV2Net((-2, -1, 3))
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_ = reverse_v2_net(x)
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assert "'axis' cannot contain duplicate dimensions" in str(info.value)
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