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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
16import numpy as np
17import pytest
18
19import mindspore.common.dtype as mstype
20import mindspore.context as context
21from mindspore.common.tensor import Tensor
22from mindspore.nn import Cell
23from mindspore.ops import operations as P
24
25class LinSpaceNet(Cell):
26    def __init__(self, num):
27        super(LinSpaceNet, self).__init__()
28        self.ls_op = P.LinSpace()
29        self.num = num
30
31    def construct(self, start, stop):
32        output = self.ls_op(start, stop, self.num)
33        return output
34
35
36@pytest.mark.level0
37@pytest.mark.platform_x86_gpu_training
38@pytest.mark.env_onecard
39def test_lin_space_1():
40    context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
41    start_np = 5
42    stop_np = 150
43    num_np = 12
44    start = Tensor(start_np, dtype=mstype.float32)
45    stop = Tensor(stop_np, dtype=mstype.float32)
46    num = num_np
47    ls_op = P.LinSpace()
48    result_ms = ls_op(start, stop, num).asnumpy()
49    result_np = np.linspace(start_np, stop_np, num_np)
50    assert np.allclose(result_ms, result_np)
51
52
53@pytest.mark.level0
54@pytest.mark.platform_x86_gpu_training
55@pytest.mark.env_onecard
56def test_lin_shape_2():
57    context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
58    start_np = -25
59    stop_np = 147
60    num_np = 10
61    start = Tensor(start_np, dtype=mstype.float32)
62    stop = Tensor(stop_np, dtype=mstype.float32)
63    num = num_np
64    ls_op = P.LinSpace()
65    result_ms = ls_op(start, stop, num).asnumpy()
66    result_np = np.linspace(start_np, stop_np, num_np)
67    assert np.allclose(result_ms, result_np)
68
69
70@pytest.mark.level0
71@pytest.mark.platform_x86_gpu_training
72@pytest.mark.env_onecard
73def test_lin_shape_3():
74    context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
75    start_np = 25
76    stop_np = -147
77    num_np = 20
78    start = Tensor(start_np, dtype=mstype.float32)
79    stop = Tensor(stop_np, dtype=mstype.float32)
80    net = LinSpaceNet(num_np)
81    result_ms = net(start, stop).asnumpy()
82    result_np = np.linspace(start_np, stop_np, num_np)
83    assert np.allclose(result_ms, result_np)
84
85
86@pytest.mark.level0
87@pytest.mark.platform_x86_gpu_training
88@pytest.mark.env_onecard
89def test_lin_shape_4():
90    context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
91    start_np = -25.3
92    stop_np = -147
93    num_np = 36
94    start = Tensor(start_np, dtype=mstype.float32)
95    stop = Tensor(stop_np, dtype=mstype.float32)
96    net = LinSpaceNet(num_np)
97    result_ms = net(start, stop).asnumpy()
98    result_np = np.linspace(start_np, stop_np, num_np)
99    assert np.allclose(result_ms, result_np)
100