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/hashtable_lookup.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 TestHashtableLookup : public UT::Common {
29 public:
TestHashtableLookup()30 TestHashtableLookup() {}
SetUp()31 void SetUp() {}
TearDown()32 void TearDown() {}
33 };
34
TEST_F(TestHashtableLookup,test_ops_hashtable_lookup1)35 TEST_F(TestHashtableLookup, test_ops_hashtable_lookup1) {
36 auto hashtable_lookup = std::make_shared<HashtableLookup>();
37 hashtable_lookup->Init();
38 auto inputs0 = TensorConstructUtils::CreateOnesTensor(kNumberTypeInt32, std::vector<int64_t>{4, 3});
39 auto inputs1 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{1});
40 auto inputs2 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{1});
41 MS_EXCEPTION_IF_NULL(inputs0);
42 MS_EXCEPTION_IF_NULL(inputs1);
43 MS_EXCEPTION_IF_NULL(inputs2);
44 auto abstract = hashtable_lookup->Infer({inputs0->ToAbstract(), inputs1->ToAbstract(), inputs2->ToAbstract()});
45 MS_EXCEPTION_IF_NULL(abstract);
46 EXPECT_EQ(abstract->isa<abstract::AbstractTuple>(), true);
47 auto shape_ptr = abstract->BuildShape();
48 MS_EXCEPTION_IF_NULL(shape_ptr);
49 EXPECT_EQ(shape_ptr->isa<abstract::TupleShape>(), true);
50 auto shape = shape_ptr->cast<abstract::TupleShapePtr>();
51 MS_EXCEPTION_IF_NULL(shape);
52 auto shape_vec = shape->shape();
53 EXPECT_EQ(shape_vec.size(), 2);
54 auto shape1 = shape_vec[0]->cast<abstract::ShapePtr>()->shape();
55 EXPECT_EQ(shape1.size(), 0);
56 auto shape2 = shape_vec[1]->cast<abstract::ShapePtr>()->shape();
57 EXPECT_EQ(shape2.size(), 1);
58 EXPECT_EQ(shape2[0], 4);
59 auto type_ptr = abstract->BuildType();
60 MS_EXCEPTION_IF_NULL(type_ptr);
61 auto type = type_ptr->cast<TuplePtr>();
62 MS_EXCEPTION_IF_NULL(type);
63 auto type_vec = type->elements();
64 MS_EXCEPTION_IF_NULL(type_vec[0]);
65 auto data0_type = type_vec[0]->cast<TensorTypePtr>()->element();
66 MS_EXCEPTION_IF_NULL(data0_type);
67 EXPECT_EQ(data0_type->type_id(), kNumberTypeFloat32);
68 MS_EXCEPTION_IF_NULL(type_vec[1]);
69 auto data1_type = type_vec[1]->cast<TensorTypePtr>()->element();
70 MS_EXCEPTION_IF_NULL(data1_type);
71 EXPECT_EQ(data1_type->type_id(), kNumberTypeInt8);
72 }
73
74 } // namespace ops
75 } // namespace mindspore
76