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 17 18import mindspore.context as context 19import mindspore.nn as nn 20from mindspore import Tensor 21from mindspore.ops import operations as P 22from mindspore.ops.operations import _grad_ops as G 23 24context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") 25 26 27class Net(nn.Cell): 28 def __init__(self): 29 super(Net, self).__init__() 30 self.cast = P.Cast() 31 self.relu = P.ReLU() 32 self.biasaddgrad = G.BiasAddGrad() 33 34 def construct(self, x): 35 x = self.relu(x) 36 x = self.relu(x) 37 x = self.relu(x) 38 x = self.biasaddgrad(x) 39 x = self.relu(x) 40 x = self.relu(x) 41 x = self.relu(x) 42 return x 43 44 45@pytest.mark.level1 46@pytest.mark.platform_arm_ascend_training 47@pytest.mark.platform_x86_ascend_training 48@pytest.mark.env_onecard 49def test_net(): 50 x = np.random.randn(32, 10).astype(np.float32) 51 net = Net() 52 output = net(Tensor(x)) 53 print(output.asnumpy()) 54