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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"""
16@File  : test_compile.py
17@Author:
18@Date  : 2019-03-20
19@Desc  : test mindspore compile method
20"""
21import logging
22import numpy as np
23
24import mindspore.nn as nn
25from mindspore import Tensor, Model, context
26from mindspore.nn.optim import Momentum
27from mindspore.ops.composite import add_flags
28from ...ut_filter import non_graph_engine
29
30log = logging.getLogger("test")
31log.setLevel(level=logging.ERROR)
32
33
34class Net(nn.Cell):
35    """ Net definition """
36
37    def __init__(self):
38        super(Net, self).__init__()
39        self.conv = nn.Conv2d(3, 64, 3, has_bias=False, weight_init='normal')
40        self.relu = nn.ReLU()
41        self.flatten = nn.Flatten()
42
43    def construct(self, x):
44        x = self.conv(x)
45        x = self.relu(x)
46        out = self.flatten(x)
47        return out
48
49
50loss = nn.MSELoss()
51
52
53# Test case 1 : test the new compiler interface
54# _build_train_graph is deprecated
55def test_build():
56    """ test_build """
57    Tensor(np.random.randint(0, 255, [1, 3, 224, 224]))
58    Tensor(np.random.randint(0, 10, [1, 10]))
59    net = Net()
60    opt = Momentum(net.get_parameters(), learning_rate=0.1, momentum=0.9)
61    Model(net, loss_fn=loss, optimizer=opt, metrics=None)
62
63
64# Test case 2 : test the use different args to run graph
65class Net2(nn.Cell):
66    """ Net2 definition """
67
68    def __init__(self):
69        super(Net2, self).__init__()
70        self.relu = nn.ReLU()
71
72    def construct(self, x):
73        x = self.relu(x)
74        return x
75
76
77@non_graph_engine
78def test_different_args_run():
79    """ test_different_args_run """
80    np1 = np.random.randn(2, 3, 4, 5).astype(np.float32)
81    input_me1 = Tensor(np1)
82    np2 = np.random.randn(2, 3, 4, 5).astype(np.float32)
83    input_me2 = Tensor(np2)
84
85    net = Net2()
86    net = add_flags(net, predit=True)
87    context.set_context(mode=context.GRAPH_MODE)
88    model = Model(net)
89    me1 = model.predict(input_me1)
90    me2 = model.predict(input_me2)
91    out_me1 = me1.asnumpy()
92    out_me2 = me2.asnumpy()
93    print(np1)
94    print(np2)
95    print(out_me1)
96    print(out_me2)
97    assert not np.allclose(out_me1, out_me2, 0.01, 0.01)
98