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 17import mindspore.context as context 18import mindspore.nn as nn 19from mindspore import Tensor 20import mindspore.common.dtype as mstype 21from mindspore.ops import operations as P 22 23context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend") 24 25class Net(nn.Cell): 26 def __init__(self): 27 super(Net, self).__init__() 28 self.unique = P.Unique() 29 30 def construct(self, x): 31 return self.unique(x) 32 33@pytest.mark.level0 34@pytest.mark.platform_arm_ascend_training 35@pytest.mark.platform_x86_ascend_training 36@pytest.mark.env_onecard 37def test_pynative_unqiue(): 38 x = Tensor(np.array([1, 1, 2, 2, 3, 3]), mstype.int32) 39 unique = Net() 40 output = unique(x) 41 expect1 = np.array([1, 2, 3]) 42 expect2 = np.array([0, 0, 1, 1, 2, 2]) 43 assert (output[0].asnumpy() == expect1).all() 44 assert (output[1].asnumpy() == expect2).all() 45