1# Copyright 2020 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 express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================ 15import numpy as np 16import pytest 17from cus_add3 import CusAdd3 18 19import mindspore.context as context 20import mindspore.nn as nn 21from mindspore import Tensor 22 23context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") 24 25 26class Net(nn.Cell): 27 """Net definition""" 28 29 def __init__(self): 30 super(Net, self).__init__() 31 self.add3 = CusAdd3(1.0) 32 33 def construct(self, input1, input2): 34 return self.add3(input1, input2) 35 36 37@pytest.mark.level0 38@pytest.mark.platform_x86_ascend_training 39@pytest.mark.platform_arm_ascend_training 40@pytest.mark.env_onecard 41def test_net(): 42 input1 = np.array([1.0, 4.0, 9.0]).astype(np.float32) 43 input2 = np.array([1.0, 2.0, 3.0]).astype(np.float32) 44 add3_net = Net() 45 output = add3_net(Tensor(input1), Tensor(input2)) 46 expect = np.array([3.0, 7.0, 13.0]).astype(np.float32) 47 assert (output.asnumpy() == expect).all() 48