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77 lines
2.6 KiB
77 lines
2.6 KiB
# Copyright 2020 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.common import dtype as mstype
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from mindspore.common.api import ms_function
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from mindspore.ops import operations as P
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from mindspore.ops.operations import _grad_ops as G
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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class StridedSliceGrad(nn.Cell):
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def __init__(self):
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super(StridedSliceGrad, self).__init__()
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self.ssg = G.StridedSliceGrad()
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self.shape = P.Shape()
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@ms_function
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def construct(self, dy, x):
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return self.ssg(dy, self.shape(x), (2, 0, 0), (3, 2, 3), (1, 1, 1))
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_slice():
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x = Tensor(np.array([[[1., 1., 1.], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]], [[5, 5, 5], [6, 7, 8]]]).astype(np.float32))
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dy = Tensor(np.array([[[5., 1., 5.], [6., 1., 8.]]]).astype(np.float32))
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ssg = StridedSliceGrad()
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output = ssg(dy, x)
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expect = [[[0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0]], [[5, 1, 5], [6, 1, 8]]]
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assert (output.asnumpy() == expect).all()
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class StridedSliceGrad2(nn.Cell):
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def __init__(self):
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super(StridedSliceGrad2, self).__init__()
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self.ssg = G.StridedSliceGrad()
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self.shape = P.Shape()
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@ms_function
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def construct(self, dy, x):
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return self.ssg(dy, self.shape(x), (0, 0, 0), (1, 4, 2), (1, 1, 1))
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_slice2():
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x = Tensor(np.arange(2 * 4 * 2).reshape(2, 4, 2), mstype.float32)
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dy = Tensor(np.arange(4 * 2).reshape(4, 2), mstype.float32)
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ssg = StridedSliceGrad2()
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output = ssg(dy, x)
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expect = [[[0., 1.], [2., 3.], [4., 5.], [6., 7.]], [[0., 0.], [0., 0.], [0., 0.], [0., 0.]]]
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assert (output.asnumpy() == expect).all()
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if __name__ == '__main__':
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test_slice()
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test_slice2()
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