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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 os
16import numpy as np
17import pytest
18
19import mindspore.nn as nn
20from mindspore import context
21from mindspore.common.tensor import Tensor
22from mindspore.common import dtype as mstype
23from mindspore.train.serialization import export, load
24
25ZERO = Tensor([0], mstype.int32)
26ONE = Tensor([1], mstype.int32)
27
28
29class RecrusiveNet(nn.Cell):
30    def construct(self, x, z):
31        def f(x, z):
32            y = ZERO
33            if x < 0:
34                y = ONE
35            elif x < 3:
36                y = x * f(x - 1, z)
37            elif x < 5:
38                y = x * f(x - 2, z)
39            else:
40                y = f(x - 4, z)
41            z = y + 1 + z
42            return z
43
44        return f(x, z)
45
46
47@pytest.mark.level0
48@pytest.mark.platform_x86_ascend_training
49@pytest.mark.platform_arm_ascend_training
50@pytest.mark.env_onecard
51def test_recrusive():
52    context.set_context(mode=context.GRAPH_MODE)
53    network = RecrusiveNet()
54
55    x = Tensor(np.array([1]).astype(np.float32))
56    y = Tensor(np.array([2]).astype(np.float32))
57    origin_out = network(x, y)
58
59    file_name = "recrusive_net"
60    export(network, x, y, file_name=file_name, file_format='MINDIR')
61    mindir_name = file_name + ".mindir"
62    assert os.path.exists(mindir_name)
63
64    graph = load(mindir_name)
65    loaded_net = nn.GraphCell(graph)
66    outputs_after_load = loaded_net(x, y)
67    assert origin_out == outputs_after_load
68