1 /**
2 * Copyright 2021 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/unsqueeze.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 class TestUnsqueeze : public UT::Common {
28 public:
TestUnsqueeze()29 TestUnsqueeze() {}
SetUp()30 void SetUp() {}
TearDown()31 void TearDown() {}
32 };
33
34 /*TEST_F(TestUnsqueeze, test_unsqueeze_1) {
35 auto unsqueeze = std::make_shared<Unsqueeze>();
36 std::vector<int64_t> axis = {};
37 unsqueeze->Init(axis);
38 auto tensor_x = std::make_shared<tensor::Tensor>(kNumberTypeFloat16, std::vector<int64_t>{1, 3, 2});
39 MS_EXCEPTION_IF_NULL(tensor_x);
40 auto tensor_x_data = reinterpret_cast<int *>(tensor_x->data_c());
41 *tensor_x_data = 1;
42 tensor_x_data++;
43 *tensor_x_data = 2;
44 tensor_x_data++;
45 *tensor_x_data = 3;
46 tensor_x_data++;
47 *tensor_x_data = 4;
48 tensor_x_data++;
49 *tensor_x_data = 5;
50 tensor_x_data++;
51 *tensor_x_data = 6;
52 tensor_x_data++;
53 auto abstract = unsqueeze->Infer({tensor_x->ToAbstract()});
54 MS_EXCEPTION_IF_NULL(abstract);
55 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true);
56 auto shape_ptr = abstract->BuildShape();
57 MS_EXCEPTION_IF_NULL(shape_ptr);
58 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true);
59 auto shape = shape_ptr->cast<abstract::ShapePtr>();
60 MS_EXCEPTION_IF_NULL(shape);
61 auto shape_vec = shape->shape();
62 EXPECT_EQ(shape_vec.size(), 2);
63 EXPECT_EQ(shape_vec[0], 3);
64 EXPECT_EQ(shape_vec[1], 2);
65 auto type = abstract->BuildType();
66 MS_EXCEPTION_IF_NULL(type);
67 EXPECT_EQ(type->isa<TensorType>(), true);
68 auto tensor_type = type->cast<TensorTypePtr>();
69 MS_EXCEPTION_IF_NULL(tensor_type);
70 auto data_type = tensor_type->element();
71 MS_EXCEPTION_IF_NULL(data_type);
72 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat16);
73 }
74 */
TEST_F(TestUnsqueeze,test_unsqueeze_1)75 TEST_F(TestUnsqueeze, test_unsqueeze_1) {
76 auto unsqueeze = std::make_shared<Unsqueeze>();
77 std::vector<int64_t> axis = {1, 2};
78 unsqueeze->Init(axis);
79 auto tensor_x = std::make_shared<tensor::Tensor>(kNumberTypeFloat32, std::vector<int64_t>{1, 3});
80 MS_EXCEPTION_IF_NULL(tensor_x);
81 auto tensor_x_data = reinterpret_cast<int *>(tensor_x->data_c());
82 *tensor_x_data = 1;
83 tensor_x_data++;
84 *tensor_x_data = 2;
85 tensor_x_data++;
86 *tensor_x_data = 3;
87 tensor_x_data++;
88 auto abstract = unsqueeze->Infer({tensor_x->ToAbstract()});
89 MS_EXCEPTION_IF_NULL(abstract);
90 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true);
91 auto shape_ptr = abstract->BuildShape();
92 MS_EXCEPTION_IF_NULL(shape_ptr);
93 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true);
94 auto shape = shape_ptr->cast<abstract::ShapePtr>();
95 MS_EXCEPTION_IF_NULL(shape);
96 auto shape_vec = shape->shape();
97 EXPECT_EQ(shape_vec.size(), 4);
98 EXPECT_EQ(shape_vec[0], 1);
99 EXPECT_EQ(shape_vec[1], 1);
100 EXPECT_EQ(shape_vec[2], 1);
101 EXPECT_EQ(shape_vec[3], 3);
102 auto type = abstract->BuildType();
103 MS_EXCEPTION_IF_NULL(type);
104 EXPECT_EQ(type->isa<TensorType>(), true);
105 auto tensor_type = type->cast<TensorTypePtr>();
106 MS_EXCEPTION_IF_NULL(tensor_type);
107 auto data_type = tensor_type->element();
108 MS_EXCEPTION_IF_NULL(data_type);
109 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32);
110 }
111 } // namespace ops
112 } // namespace mindspore
113