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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# ============================================================================
15import numpy as np
16import pytest
17import mindspore.context as context
18import mindspore.nn as nn
19from mindspore import Tensor
20from mindspore.ops import operations as P
21
22
23class Net(nn.Cell):
24    def __init__(self):
25        super(Net, self).__init__()
26        self.ops = P.Less()
27
28    def construct(self, x, y):
29        return self.ops(x, y)
30
31
32@pytest.mark.level0
33@pytest.mark.platform_x86_cpu
34@pytest.mark.env_onecard
35def test_net():
36    x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
37    y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
38    x1_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
39    y1_np = np.random.randint(1, 5, (2, 1, 4, 4)).astype(np.float32)
40    x2_np = np.random.randint(1, 5, (2, 1, 1, 4)).astype(np.float32)
41    y2_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
42    x3_np = np.random.randint(1, 5, 1).astype(np.float32)
43    y3_np = np.random.randint(1, 5, 1).astype(np.float32)
44    x4_np = np.array(768).astype(np.float32)
45    y4_np = np.array(3072.5).astype(np.float32)
46
47    x0 = Tensor(x0_np)
48    y0 = Tensor(y0_np)
49    x1 = Tensor(x1_np)
50    y1 = Tensor(y1_np)
51    x2 = Tensor(x2_np)
52    y2 = Tensor(y2_np)
53    x3 = Tensor(x3_np)
54    y3 = Tensor(y3_np)
55    x4 = Tensor(x4_np)
56    y4 = Tensor(y4_np)
57
58    context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
59    net = Net()
60    out = net(x0, y0).asnumpy()
61    expect = x0_np < y0_np
62    assert np.all(out == expect)
63    assert out.shape == expect.shape
64
65    out = net(x1, y1).asnumpy()
66    expect = x1_np < y1_np
67    assert np.all(out == expect)
68    assert out.shape == expect.shape
69
70    out = net(x2, y2).asnumpy()
71    expect = x2_np < y2_np
72    assert np.all(out == expect)
73    assert out.shape == expect.shape
74
75    out = net(x3, y3).asnumpy()
76    expect = x3_np < y3_np
77    assert np.all(out == expect)
78    assert out.shape == expect.shape
79
80    out = net(x4, y4).asnumpy()
81    expect = x4_np < y4_np
82    assert np.all(out == expect)
83    assert out.shape == expect.shape
84