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1# Copyright 2021 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# ============================================================================
15
16import pytest
17import mindspore.context as context
18import mindspore.nn as nn
19from mindspore import Tensor
20from mindspore.common import 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, shape, seed=0, seed2=0):
28        super(Net, self).__init__()
29        self.shape = shape
30        self.min_val = Tensor(10, mstype.int32)
31        self.max_val = Tensor(100, mstype.int32)
32        self.seed = seed
33        self.seed2 = seed2
34        self.uniformint = P.UniformInt(seed, seed2)
35
36    def construct(self):
37        return self.uniformint(self.shape, self.min_val, self.max_val)
38
39
40@pytest.mark.level0
41@pytest.mark.platform_x86_cpu
42@pytest.mark.env_onecard
43def test_net():
44    seed = 10
45    seed2 = 10
46    shape = (5, 6, 8)
47    net = Net(shape, seed, seed2)
48    output = net()
49    assert output.shape == (5, 6, 8)
50    outnumpyflatten_1 = output.asnumpy().flatten()
51
52    seed = 0
53    seed2 = 10
54    shape = (5, 6, 8)
55    net = Net(shape, seed, seed2)
56    output = net()
57    assert output.shape == (5, 6, 8)
58    outnumpyflatten_2 = output.asnumpy().flatten()
59    # same seed should generate same random number
60    assert (outnumpyflatten_1 == outnumpyflatten_2).all()
61
62    seed = 0
63    seed2 = 0
64    shape = (130, 120, 141)
65    net = Net(shape, seed, seed2)
66    output = net()
67    assert output.shape == (130, 120, 141)
68