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58 lines
1.9 KiB
58 lines
1.9 KiB
# Copyright 2019 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 matrix_inverseress 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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from numpy.linalg import inv
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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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np.random.seed(1)
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class NetMatrixInverse(nn.Cell):
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def __init__(self):
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super(NetMatrixInverse, self).__init__()
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self.matrix_inverse = P.MatrixInverse()
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def construct(self, x):
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return self.matrix_inverse(x)
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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_matrix_inverse():
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x0_np = np.random.uniform(-2, 2, (3, 4, 4)).astype(np.float32)
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x0 = Tensor(x0_np)
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expect0 = inv(x0_np)
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error0 = np.ones(shape=expect0.shape) * 1.0e-3
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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matrix_inverse = NetMatrixInverse()
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output0 = matrix_inverse(x0)
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diff0 = output0.asnumpy() - expect0
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assert np.all(diff0 < error0)
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assert output0.shape == expect0.shape
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
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matrix_inverse = NetMatrixInverse()
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output0 = matrix_inverse(x0)
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diff0 = output0.asnumpy() - expect0
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assert np.all(diff0 < error0)
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assert output0.shape == expect0.shape
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