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76 lines
2.8 KiB
76 lines
2.8 KiB
/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <vector>
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#include <memory>
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#include "common/common_test.h"
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#include "ops/hashtable_lookup.h"
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#include "ir/dtype/type.h"
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#include "ir/value.h"
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#include "abstract/dshape.h"
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#include "utils/tensor_construct_utils.h"
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namespace mindspore {
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namespace ops {
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class TestHashtableLookup : public UT::Common {
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public:
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TestHashtableLookup() {}
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void SetUp() {}
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void TearDown() {}
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};
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TEST_F(TestHashtableLookup, test_ops_hashtable_lookup1) {
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auto hashtable_lookup = std::make_shared<HashtableLookup>();
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hashtable_lookup->Init();
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auto inputs0 = TensorConstructUtils::CreateOnesTensor(kNumberTypeInt32, std::vector<int64_t>{4, 3});
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auto inputs1 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{1});
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auto inputs2 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{1});
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MS_EXCEPTION_IF_NULL(inputs0);
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MS_EXCEPTION_IF_NULL(inputs1);
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MS_EXCEPTION_IF_NULL(inputs2);
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auto abstract = hashtable_lookup->Infer({inputs0->ToAbstract(), inputs1->ToAbstract(), inputs2->ToAbstract()});
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MS_EXCEPTION_IF_NULL(abstract);
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EXPECT_EQ(abstract->isa<abstract::AbstractTuple>(), true);
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auto shape_ptr = abstract->BuildShape();
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MS_EXCEPTION_IF_NULL(shape_ptr);
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EXPECT_EQ(shape_ptr->isa<abstract::TupleShape>(), true);
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auto shape = shape_ptr->cast<abstract::TupleShapePtr>();
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MS_EXCEPTION_IF_NULL(shape);
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auto shape_vec = shape->shape();
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EXPECT_EQ(shape_vec.size(), 2);
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auto shape1 = shape_vec[0]->cast<abstract::ShapePtr>()->shape();
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EXPECT_EQ(shape1.size(), 0);
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auto shape2 = shape_vec[1]->cast<abstract::ShapePtr>()->shape();
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EXPECT_EQ(shape2.size(), 1);
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EXPECT_EQ(shape2[0], 4);
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auto type_ptr = abstract->BuildType();
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MS_EXCEPTION_IF_NULL(type_ptr);
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auto type = type_ptr->cast<TuplePtr>();
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MS_EXCEPTION_IF_NULL(type);
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auto type_vec = type->elements();
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MS_EXCEPTION_IF_NULL(type_vec[0]);
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auto data0_type = type_vec[0]->cast<TensorTypePtr>()->element();
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MS_EXCEPTION_IF_NULL(data0_type);
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EXPECT_EQ(data0_type->type_id(), kNumberTypeFloat32);
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MS_EXCEPTION_IF_NULL(type_vec[1]);
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auto data1_type = type_vec[1]->cast<TensorTypePtr>()->element();
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MS_EXCEPTION_IF_NULL(data1_type);
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EXPECT_EQ(data1_type->type_id(), kNumberTypeInt8);
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}
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} // namespace ops
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} // namespace mindspore
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