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, Parameter 20import mindspore.common.dtype as mstype 21from mindspore.ops import operations as P 22 23context.set_context(mode=context.GRAPH_MODE, device_target="CPU") 24 25 26class Net(nn.Cell): 27 def __init__(self): 28 super(Net, self).__init__() 29 self.unique = P.Unique() 30 self.dynamic_assign = P.DynamicAssign() 31 self.param = Parameter( 32 Tensor(np.zeros((5,), np.int32)), name="assign_x") 33 34 def construct(self, y): 35 y, _ = self.unique(y) 36 return self.dynamic_assign(self.param, y) 37 38 39@pytest.mark.level0 40@pytest.mark.platform_arm_ascend_training 41@pytest.mark.platform_x86_ascend_training 42@pytest.mark.env_onecard 43def test_dynamic_assign(): 44 y = Tensor(np.array([2, 2, 3, 3, 4]), mstype.int32) 45 dynamic_assign = Net() 46 _ = dynamic_assign(y) 47 expect1 = np.array([2, 3, 4]) 48 param_np = dynamic_assign.param.data.asnumpy() 49 assert (param_np == expect1).all() 50