1# Copyright 2019 Huawei Technologies Co., Ltd 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either matrix_inverseress or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================ 15 16import numpy as np 17from numpy.linalg import inv 18import pytest 19 20import mindspore.context as context 21import mindspore.nn as nn 22from mindspore import Tensor 23from mindspore.ops import operations as P 24 25np.random.seed(1) 26 27class NetMatrixInverse(nn.Cell): 28 def __init__(self): 29 super(NetMatrixInverse, self).__init__() 30 self.matrix_inverse = P.MatrixInverse() 31 32 def construct(self, x): 33 return self.matrix_inverse(x) 34 35 36@pytest.mark.level0 37@pytest.mark.platform_x86_gpu_training 38@pytest.mark.env_onecard 39def test_matrix_inverse(): 40 x0_np = np.random.uniform(-2, 2, (3, 4, 4)).astype(np.float32) 41 x0 = Tensor(x0_np) 42 expect0 = inv(x0_np) 43 error0 = np.ones(shape=expect0.shape) * 1.0e-3 44 45 context.set_context(mode=context.GRAPH_MODE, device_target="GPU") 46 matrix_inverse = NetMatrixInverse() 47 output0 = matrix_inverse(x0) 48 diff0 = output0.asnumpy() - expect0 49 assert np.all(diff0 < error0) 50 assert output0.shape == expect0.shape 51 52 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU") 53 matrix_inverse = NetMatrixInverse() 54 output0 = matrix_inverse(x0) 55 diff0 = output0.asnumpy() - expect0 56 assert np.all(diff0 < error0) 57 assert output0.shape == expect0.shape 58