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: 30 TestHashtableLookup() {} 31 void SetUp() {} 32 void TearDown() {} 33 }; 34 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