forked from mindspore-Ecosystem/mindspore
50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
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# Copyright 2023 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 as ms
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import mindspore.nn as nn
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class NetMatrixPower(nn.Cell):
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def construct(self, x, n):
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return x.matrix_power(n)
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@pytest.mark.level1
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
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def test_matrix_power(mode):
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"""
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Feature: Tensor.matrix_power
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Description: Verify the result of matrix_power
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Expectation: success.
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"""
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ms.set_context(mode=mode)
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arrs = [
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np.random.rand(1, 2, 2).astype('float32'),
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np.random.rand(2, 3, 3).astype('float32'),
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np.random.rand(3, 4, 4).astype('float32'),
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]
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net_matrix_power = NetMatrixPower()
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for arr in arrs:
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for n in range(0, 4):
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expect_out = np.linalg.matrix_power(arr, n)
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out = net_matrix_power(ms.Tensor(arr), n)
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assert np.allclose(out.asnumpy(), expect_out, rtol=1e-4, atol=1e-4)
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