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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# ============================================================================
15""" Test Interpolate """
16import pytest
17
18import mindspore.nn as nn
19import mindspore.common.dtype as mstype
20from mindspore import Tensor
21from mindspore import context
22
23context.set_context(mode=context.GRAPH_MODE)
24
25
26def test_resizebilinear():
27    class Net(nn.Cell):
28        def __init__(self):
29            super(Net, self).__init__()
30            self.value = Tensor([[[[1, 2, 3, 4], [5, 6, 7, 8]]]], mstype.float32)
31
32        def construct(self):
33            interpolate = nn.ResizeBilinear()
34            return interpolate(self.value, size=(5, 5))
35
36    net = Net()
37    net()
38
39
40def test_resizebilinear_1():
41    class Net(nn.Cell):
42        def __init__(self):
43            super(Net, self).__init__()
44            self.value = Tensor([[[[1, 2, 3, 4], [5, 6, 7, 8]]]], mstype.float32)
45
46        def construct(self):
47            interpolate = nn.ResizeBilinear()
48            return interpolate(self.value, scale_factor=2)
49
50    net = Net()
51    net()
52
53
54def test_resizebilinear_parameter():
55    class Net(nn.Cell):
56        def __init__(self):
57            super(Net, self).__init__()
58
59        def construct(self, x):
60            interpolate = nn.ResizeBilinear()
61            return interpolate(x, size=(5, 5))
62
63    net = Net()
64    net(Tensor([[[[1, 2, 3, 4], [5, 6, 7, 8]]]], mstype.float32))
65
66
67def test_resizebilinear_parameter_1():
68    class Net(nn.Cell):
69        def __init__(self):
70            super(Net, self).__init__()
71
72        def construct(self, x):
73            interpolate = nn.ResizeBilinear()
74            return interpolate(x, scale_factor=2)
75
76    net = Net()
77    net(Tensor([[[[1, 2, 3, 4], [5, 6, 7, 8]]]], mstype.float32))
78
79
80def test_resizebilinear_error():
81    class Net(nn.Cell):
82        def __init__(self):
83            super(Net, self).__init__()
84            self.value = Tensor([[[[1, 2, 3, 4], [5, 6, 7, 8]]]], mstype.float32)
85
86        def construct(self):
87            interpolate = nn.ResizeBilinear()
88            return interpolate(self.value)
89
90    net = Net()
91    with pytest.raises(ValueError) as ex:
92        net()
93    assert "'size' and 'scale' both none" in str(ex.value)
94
95
96def test_resizebilinear_error_1():
97    class Net(nn.Cell):
98        def __init__(self):
99            super(Net, self).__init__()
100            self.value = Tensor([[[[1, 2, 3, 4], [5, 6, 7, 8]]]], mstype.float32)
101
102        def construct(self):
103            interpolate = nn.ResizeBilinear()
104            return interpolate(self.value, size=(5, 5), scale_factor=2)
105
106    net = Net()
107    with pytest.raises(ValueError) as ex:
108        net()
109    assert "'size' and 'scale' both not none" in str(ex.value)
110