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1 /**
2  * Copyright 2020 Huawei Technologies Co., Ltd
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  * http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 #include <vector>
17 #include <memory>
18 #include "common/common_test.h"
19 #include "ops/custom_predict.h"
20 #include "ir/dtype/type.h"
21 #include "ir/value.h"
22 #include "abstract/dshape.h"
23 #include "utils/tensor_construct_utils.h"
24 
25 namespace mindspore {
26 namespace ops {
27 
28 class TestCustomPredict : public UT::Common {
29  public:
30   TestCustomPredict() {}
31   void SetUp() {}
32   void TearDown() {}
33 };
34 
35 TEST_F(TestCustomPredict, test_ops_custom_predict1) {
36   auto custom_predict = std::make_shared<CustomPredict>();
37   custom_predict->Init(5, 0.1);
38   EXPECT_EQ(custom_predict->get_output_num(), 5);
39   EXPECT_EQ((int64_t)(custom_predict->get_weight_threshold() - 0.1), 0);
40   auto inputs0 = TensorConstructUtils::CreateOnesTensor(kNumberTypeInt32, std::vector<int64_t>{1});
41   MS_EXCEPTION_IF_NULL(inputs0);
42   auto abstract = custom_predict->Infer({inputs0->ToAbstract()});
43   MS_EXCEPTION_IF_NULL(abstract);
44   EXPECT_EQ(abstract->isa<abstract::AbstractTuple>(), true);
45   auto shape_ptr = abstract->BuildShape();
46   MS_EXCEPTION_IF_NULL(shape_ptr);
47   EXPECT_EQ(shape_ptr->isa<abstract::TupleShape>(), true);
48   auto shape = shape_ptr->cast<abstract::TupleShapePtr>();
49   MS_EXCEPTION_IF_NULL(shape);
50   auto shape_vec = shape->shape();
51   EXPECT_EQ(shape_vec.size(), 2);
52   auto shape1 = shape_vec[0]->cast<abstract::ShapePtr>()->shape();
53   EXPECT_EQ(shape1.size(), 1);
54   EXPECT_EQ(shape1[0], 5);
55   auto shape2 = shape_vec[1]->cast<abstract::ShapePtr>()->shape();
56   EXPECT_EQ(shape2.size(), 1);
57   EXPECT_EQ(shape2[0], 5);
58   auto type_ptr = abstract->BuildType();
59   MS_EXCEPTION_IF_NULL(type_ptr);
60   auto type = type_ptr->cast<TuplePtr>();
61   MS_EXCEPTION_IF_NULL(type);
62   auto type_vec = type->elements();
63   MS_EXCEPTION_IF_NULL(type_vec[0]);
64   auto data0_type = type_vec[0]->cast<TensorTypePtr>()->element();
65   MS_EXCEPTION_IF_NULL(data0_type);
66   EXPECT_EQ(data0_type->type_id(), kNumberTypeInt32);
67   MS_EXCEPTION_IF_NULL(type_vec[1]);
68   auto data1_type = type_vec[1]->cast<TensorTypePtr>()->element();
69   MS_EXCEPTION_IF_NULL(data1_type);
70   EXPECT_EQ(data1_type->type_id(), kNumberTypeFloat32);
71 }
72 
73 }  // namespace ops
74 }  // namespace mindspore
75