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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
16
17import mindspore as ms
18from mindspore import context, Tensor
19from mindspore.common.api import _cell_graph_executor
20from mindspore.nn import Cell
21from mindspore.ops import operations as P
22
23
24class Net(Cell):
25    def __init__(self, strategy1=None, strategy2=None, axis=()):
26        super().__init__()
27        self.squeeze = P.Squeeze(axis=axis).shard(strategy1)
28        self.mul = P.Mul().shard(strategy2)
29
30    def construct(self, x, b):
31        out = self.squeeze(x)
32        out = self.mul(out, b)
33        return out
34
35
36_x = Tensor(np.ones([64, 1, 32, 1]), dtype=ms.float32)
37_b = Tensor(np.ones([64, 32]), dtype=ms.float32)
38
39
40def compile_net(net):
41    net.set_auto_parallel()
42    net.set_train()
43    _cell_graph_executor.compile(net, _x, _b)
44    context.reset_auto_parallel_context()
45
46
47def test_squeeze_data_parallel():
48    context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
49    strategy1 = ((16, 1, 1, 1),)
50    strategy2 = ((16, 1), (16, 1))
51    net = Net(strategy1, strategy2)
52    compile_net(net)
53
54
55def test_squeeze_model_parallel():
56    context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
57    strategy1 = ((1, 1, 16, 1),)
58    strategy2 = ((1, 16), (1, 16))
59    net = Net(strategy1, strategy2)
60    compile_net(net)
61
62
63def test_squeeze_specified_axis():
64    context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
65    strategy1 = ((4, 1, 4, 1),)
66    strategy2 = ((8, 2), (8, 2))
67    net = Net(strategy1, strategy2, (1, 3))
68    compile_net(net)
69
70
71def test_squeeze_auto_parallel():
72    context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=16, global_rank=0)
73    net = Net()
74    compile_net(net)
75
76
77def test_squeeze_repeat_calc():
78    context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
79    strategy1 = ((1, 1, 8, 1),)
80    strategy2 = ((2, 8), (2, 8))
81    net = Net(strategy1, strategy2)
82    compile_net(net)
83