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1# Copyright 2019-2021 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 numpy as np
17import pytest
18
19import mindspore.context as context
20import mindspore.nn as nn
21from mindspore import Tensor
22from mindspore.common.api import ms_function
23from mindspore.common.initializer import initializer
24from mindspore.common.parameter import Parameter
25from mindspore.ops import operations as P
26from mindspore.ops.operations import _inner_ops as inner
27
28class AddNet(nn.Cell):
29    def __init__(self, nptype):
30        super(AddNet, self).__init__()
31
32        self.add = P.Add()
33
34        np.random.seed(0)
35        self.x = Parameter(initializer(
36            Tensor(np.random.randn(2, 0).astype(nptype)), [2, 0]), name='x')
37        self.y = Parameter(initializer(
38            Tensor(np.random.randn(2, 1).astype(nptype)), [2, 1]), name='y')
39
40        self.x1 = Parameter(initializer(
41            Tensor(np.arange(3).reshape(3).astype(nptype)), [3]), name='x1')
42        self.y1 = Parameter(initializer(
43            Tensor(np.array([2]).astype(nptype)), [1]), name='y1')
44
45        self.x2 = Parameter(initializer(
46            Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype)), [3, 3, 3, 3]), name='x2')
47        self.y2 = Parameter(initializer(
48            Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype)), [3, 3, 3, 3]), name='y2')
49
50        self.x3 = Parameter(initializer(
51            Tensor(np.arange(1 * 1 * 3 * 3).reshape(1, 1, 3, 3).astype(nptype)), [1, 1, 3, 3]), name='x3')
52        self.y3 = Parameter(initializer(
53            Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype)), [3, 3, 3, 3]), name='y3')
54
55    @ms_function
56    def construct(self):
57        return (
58            self.add(self.x, self.y), self.add(self.x1, self.y1), self.add(self.x2, self.y2),
59            self.add(self.x3, self.y3))
60
61
62def add(nptype):
63    context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
64
65    add_net = AddNet(nptype)
66    output = add_net()
67    expect0 = np.array([])
68    expect1 = np.array([2, 3, 4]).astype(nptype)
69    expect2 = np.array(
70        [[[[0., 2., 4.],
71           [6., 8., 10.],
72           [12., 14., 16.]],
73          [[18., 20., 22.],
74           [24., 26., 28.],
75           [30., 32., 34.]],
76          [[36., 38., 40.],
77           [42., 44., 46.],
78           [48., 50., 52.]]],
79         [[[54., 56., 58.],
80           [60., 62., 64.],
81           [66., 68., 70.]],
82          [[72., 74., 76.],
83           [78., 80., 82.],
84           [84., 86., 88.]],
85          [[90., 92., 94.],
86           [96., 98., 100.],
87           [102., 104., 106.]]],
88         [[[108., 110., 112.],
89           [114., 116., 118.],
90           [120., 122., 124.]],
91          [[126., 128., 130.],
92           [132., 134., 136.],
93           [138., 140., 142.]],
94          [[144., 146., 148.],
95           [150., 152., 154.],
96           [156., 158., 160.]]]]).astype(nptype)
97    expect3 = np.array(
98        [[[[0., 2., 4.],
99           [6., 8., 10.],
100           [12., 14., 16.]],
101          [[9., 11., 13.],
102           [15., 17., 19.],
103           [21., 23., 25.]],
104          [[18., 20., 22.],
105           [24., 26., 28.],
106           [30., 32., 34.]]],
107         [[[27., 29., 31.],
108           [33., 35., 37.],
109           [39., 41., 43.]],
110          [[36., 38., 40.],
111           [42., 44., 46.],
112           [48., 50., 52.]],
113          [[45., 47., 49.],
114           [51., 53., 55.],
115           [57., 59., 61.]]],
116         [[[54., 56., 58.],
117           [60., 62., 64.],
118           [66., 68., 70.]],
119          [[63., 65., 67.],
120           [69., 71., 73.],
121           [75., 77., 79.]],
122          [[72., 74., 76.],
123           [78., 80., 82.],
124           [84., 86., 88.]]]]).astype(nptype)
125    assert (output[0].asnumpy() == expect0).all()
126    assert (output[1].asnumpy() == expect1).all()
127    assert (output[2].asnumpy() == expect2).all()
128    assert (output[3].asnumpy() == expect3).all()
129
130
131@pytest.mark.skip(reason='0 in shape is not support')
132@pytest.mark.level0
133@pytest.mark.platform_x86_gpu_training
134@pytest.mark.env_onecard
135def test_add_float64():
136    add(np.float64)
137
138
139@pytest.mark.skip(reason='0 in shape is not support')
140@pytest.mark.level0
141@pytest.mark.platform_x86_gpu_training
142@pytest.mark.env_onecard
143def test_add_float32():
144    add(np.float32)
145
146
147@pytest.mark.skip(reason='0 in shape is not support')
148@pytest.mark.level1
149@pytest.mark.platform_x86_gpu_training
150@pytest.mark.env_onecard
151def test_add_float16():
152    add(np.float16)
153
154
155@pytest.mark.skip(reason='0 in shape is not support')
156@pytest.mark.level1
157@pytest.mark.platform_x86_gpu_training
158@pytest.mark.env_onecard
159def test_add_int64():
160    add(np.int64)
161
162@pytest.mark.skip(reason='0 in shape is not support')
163@pytest.mark.level1
164@pytest.mark.platform_x86_gpu_training
165@pytest.mark.env_onecard
166def test_add_int32():
167    add(np.int32)
168
169class Tensoradd_d(nn.Cell):
170    def __init__(self):
171        super(Tensoradd_d, self).__init__()
172        self.test_dynamic = inner.GpuConvertToDynamicShape()
173        self.add = P.Add()
174
175    def construct(self, x, y):
176        x = self.test_dynamic(x)
177        y = self.test_dynamic(y)
178        return self.add(x, y)
179
180
181def add_dynamic(nptype):
182    context.set_context(device_target='GPU', mode=context.GRAPH_MODE)
183    net = Tensoradd_d()
184
185    x1 = Tensor(np.arange(3).reshape(3).astype(nptype))
186    y1 = Tensor(np.array([2]).astype(nptype))
187
188    x2 = Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype))
189    y2 = Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype))
190
191    expect1 = np.array([2, 3, 4])
192    expect2 = np.array(
193        [[[[0., 2., 4.],
194           [6., 8., 10.],
195           [12., 14., 16.]],
196          [[18., 20., 22.],
197           [24., 26., 28.],
198           [30., 32., 34.]],
199          [[36., 38., 40.],
200           [42., 44., 46.],
201           [48., 50., 52.]]],
202         [[[54., 56., 58.],
203           [60., 62., 64.],
204           [66., 68., 70.]],
205          [[72., 74., 76.],
206           [78., 80., 82.],
207           [84., 86., 88.]],
208          [[90., 92., 94.],
209           [96., 98., 100.],
210           [102., 104., 106.]]],
211         [[[108., 110., 112.],
212           [114., 116., 118.],
213           [120., 122., 124.]],
214          [[126., 128., 130.],
215           [132., 134., 136.],
216           [138., 140., 142.]],
217          [[144., 146., 148.],
218           [150., 152., 154.],
219           [156., 158., 160.]]]])
220
221    output1 = net(x1, y1)
222    output2 = net(x2, y2)
223    assert (output1.asnumpy() == expect1).all()
224    assert (output2.asnumpy() == expect2).all()
225
226@pytest.mark.level0
227@pytest.mark.platform_x86_gpu_training
228@pytest.mark.env_onecard
229def test_add_dynamic_float64():
230    add_dynamic(np.float64)
231
232@pytest.mark.level0
233@pytest.mark.platform_x86_gpu_training
234@pytest.mark.env_onecard
235def test_add_dynamic_float32():
236    add_dynamic(np.float32)
237
238@pytest.mark.level1
239@pytest.mark.platform_x86_gpu_training
240@pytest.mark.env_onecard
241def test_add_dynamic_float16():
242    add_dynamic(np.float16)
243
244@pytest.mark.level1
245@pytest.mark.platform_x86_gpu_training
246@pytest.mark.env_onecard
247def test_add_dynamic_int64():
248    add_dynamic(np.int64)
249
250@pytest.mark.level1
251@pytest.mark.platform_x86_gpu_training
252@pytest.mark.env_onecard
253def test_add_dynamic_int32():
254    add_dynamic(np.int32)
255