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/topk.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 TestTopK : public UT::Common {
28 public:
TestTopK()29 TestTopK() {}
SetUp()30 void SetUp() {}
TearDown()31 void TearDown() {}
32 };
33
TEST_F(TestTopK,test_topk)34 TEST_F(TestTopK, test_topk) {
35 auto topk = std::make_shared<TopK>();
36 bool sorted = true;
37 topk->Init(sorted);
38 EXPECT_EQ(topk->get_sorted(), true);
39 auto tensor_x = std::make_shared<tensor::Tensor>(kNumberTypeFloat16, std::vector<int64_t>{5});
40 MS_EXCEPTION_IF_NULL(tensor_x);
41 auto tensor_x_data = reinterpret_cast<int *>(tensor_x->data_c());
42 *tensor_x_data = 1;
43 tensor_x_data++;
44 *tensor_x_data = 2;
45 tensor_x_data++;
46 *tensor_x_data = 3;
47 tensor_x_data++;
48 *tensor_x_data = 4;
49 tensor_x_data++;
50 *tensor_x_data = 5;
51 tensor_x_data++;
52 auto k = MakeValue(3);
53 MS_EXCEPTION_IF_NULL(k);
54 auto abstract = topk->Infer({tensor_x->ToAbstract(), k->ToAbstract()});
55 MS_EXCEPTION_IF_NULL(abstract);
56 EXPECT_EQ(abstract->isa<abstract::AbstractTuple>(), true);
57 auto shape_ptr = abstract->BuildShape();
58 MS_EXCEPTION_IF_NULL(shape_ptr);
59 EXPECT_EQ(shape_ptr->isa<abstract::TupleShape>(), true);
60 auto shape = shape_ptr->cast<abstract::TupleShapePtr>();
61 MS_EXCEPTION_IF_NULL(shape);
62 auto shape_vec = shape->shape();
63 EXPECT_EQ(shape_vec.size(), 2);
64 auto shape1 = shape_vec[0]->cast<abstract::ShapePtr>()->shape();
65 EXPECT_EQ(shape1.size(), 1);
66 EXPECT_EQ(shape1[0], 3);
67 auto shape2 = shape_vec[1]->cast<abstract::ShapePtr>()->shape();
68 EXPECT_EQ(shape2.size(), 1);
69 EXPECT_EQ(shape2[0], 3);
70 auto type_ptr = abstract->BuildType();
71 MS_EXCEPTION_IF_NULL(type_ptr);
72 auto type = type_ptr->cast<TuplePtr>();
73 auto type_vec = type->elements();
74 EXPECT_EQ(type_vec.size(), 2);
75 MS_EXCEPTION_IF_NULL(type_vec[0]);
76 auto data_type1 = type_vec[0]->cast<TensorTypePtr>()->element();
77 MS_EXCEPTION_IF_NULL(data_type1);
78 EXPECT_EQ(data_type1->type_id(), kNumberTypeFloat16);
79 auto data_type2 = type_vec[1]->cast<TensorTypePtr>()->element();
80 MS_EXCEPTION_IF_NULL(data_type2);
81 EXPECT_EQ(data_type2->type_id(), kNumberTypeInt32);
82 }
83 } // namespace ops
84 } // namespace mindspore
85