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 22 23context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") 24 25 26class Net(nn.Cell): 27 def __init__(self): 28 super(Net, self).__init__() 29 self.softmax = P.Softmax(axis=1) 30 self.relu = P.ReLU() 31 self.cast = P.Cast() 32 33 def construct(self, x): 34 x = self.relu(x) 35 x = self.relu(x) 36 return x 37 38 39@pytest.mark.level1 40@pytest.mark.platform_arm_ascend_training 41@pytest.mark.platform_x86_ascend_training 42@pytest.mark.env_onecard 43def test_net(): 44 x = np.random.randn(32, 10).astype(np.float32) 45 relu_relu = Net() 46 output = relu_relu(Tensor(x)) 47 print(output.asnumpy()) 48