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75 lines
2.6 KiB
75 lines
2.6 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/merge.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 TestMerge : public UT::Common {
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public:
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TestMerge() {}
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void SetUp() {}
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void TearDown() {}
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};
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TEST_F(TestMerge, test_ops_merge1) {
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auto merge = std::make_shared<Merge>();
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merge->Init();
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auto input_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{2, 4});
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auto input_y = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{2, 4});
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MS_EXCEPTION_IF_NULL(input_x);
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MS_EXCEPTION_IF_NULL(input_y);
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std::vector<ValuePtr> inputs_ = {input_x, input_y};
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auto input = std::make_shared<ValueTuple>(inputs_);
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auto abstract = merge->Infer({input->ToAbstract()});
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MS_EXCEPTION_IF_NULL(abstract);
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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(), 2);
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EXPECT_EQ(shape1[0], 2);
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EXPECT_EQ(shape1[1], 4);
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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], 1);
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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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auto type_vec = type->elements();
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MS_EXCEPTION_IF_NULL(type_vec[0]);
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auto data_type1 = type_vec[0]->cast<TensorTypePtr>()->element();
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MS_EXCEPTION_IF_NULL(data_type1);
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EXPECT_EQ(data_type1->type_id(), kNumberTypeFloat32);
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auto data_type2 = type_vec[1]->cast<TensorTypePtr>()->element();
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MS_EXCEPTION_IF_NULL(data_type2);
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EXPECT_EQ(data_type2->type_id(), kNumberTypeInt32);
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}
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} // namespace ops
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} // namespace mindspore
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