mindspore/tests/ut/cpp/ops/test_ops_where.cc

96 lines
3.6 KiB
C++

/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <vector>
#include <memory>
#include "common/common_test.h"
#include "ops/where.h"
#include "ir/dtype/type.h"
#include "ir/value.h"
#include "abstract/dshape.h"
#include "utils/tensor_construct_utils.h"
namespace mindspore {
namespace ops {
class TestWhere : public UT::Common {
public:
TestWhere() {}
void SetUp() {}
void TearDown() {}
};
TEST_F(TestWhere, test_ops_where1) {
// auto where = std::make_shared<Where>();
// where->Init();
// auto inputs0 = TensorConstructUtils::CreateOnesTensor(kNumberTypeInt64, std::vector<int64_t>{2, 3});
// auto inputs1 = TensorConstructUtils::CreateOnesTensor(kNumberTypeInt64, std::vector<int64_t>{2, 3});
// MS_EXCEPTION_IF_NULL(inputs0);
// MS_EXCEPTION_IF_NULL(inputs1);
// auto abstract = where->Infer({inputs0->ToAbstract(), inputs1->ToAbstract()});
// MS_EXCEPTION_IF_NULL(abstract);
// EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true);
// auto shape_ptr = abstract->BuildShape();
// MS_EXCEPTION_IF_NULL(shape_ptr);
// EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true);
// auto shape = shape_ptr->cast<abstract::ShapePtr>();
// MS_EXCEPTION_IF_NULL(shape);
// auto shape_vec = shape->shape();
// EXPECT_EQ(shape_vec.size(), 2);
// EXPECT_EQ(shape_vec[0], 2);
// EXPECT_EQ(shape_vec[1], 3);
// auto type = abstract->BuildType();
// MS_EXCEPTION_IF_NULL(type);
// EXPECT_EQ(type->isa<TensorType>(), true);
// auto tensor_type = type->cast<TensorTypePtr>();
// MS_EXCEPTION_IF_NULL(tensor_type);
// auto data_type = tensor_type->element();
// MS_EXCEPTION_IF_NULL(data_type);
// EXPECT_EQ(data_type->type_id(), kNumberTypeInt64);
}
TEST_F(TestWhere, test_ops_where2) {
auto where = std::make_shared<Where>();
where->Init();
auto inputs0 = TensorConstructUtils::CreateOnesTensor(kNumberTypeInt64, std::vector<int64_t>{1});
auto inputs1 = TensorConstructUtils::CreateOnesTensor(kNumberTypeInt64, std::vector<int64_t>{4});
auto inputs2 = TensorConstructUtils::CreateOnesTensor(kNumberTypeInt64, std::vector<int64_t>{1});
MS_EXCEPTION_IF_NULL(inputs0);
MS_EXCEPTION_IF_NULL(inputs1);
MS_EXCEPTION_IF_NULL(inputs2);
auto abstract = where->Infer({inputs0->ToAbstract(), inputs1->ToAbstract(), inputs2->ToAbstract()});
MS_EXCEPTION_IF_NULL(abstract);
EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true);
auto shape_ptr = abstract->BuildShape();
MS_EXCEPTION_IF_NULL(shape_ptr);
EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true);
auto shape = shape_ptr->cast<abstract::ShapePtr>();
MS_EXCEPTION_IF_NULL(shape);
auto shape_vec = shape->shape();
EXPECT_EQ(shape_vec.size(), 1);
EXPECT_EQ(shape_vec[0], 4);
auto type = abstract->BuildType();
MS_EXCEPTION_IF_NULL(type);
EXPECT_EQ(type->isa<TensorType>(), true);
auto tensor_type = type->cast<TensorTypePtr>();
MS_EXCEPTION_IF_NULL(tensor_type);
auto data_type = tensor_type->element();
MS_EXCEPTION_IF_NULL(data_type);
EXPECT_EQ(data_type->type_id(), kNumberTypeInt64);
}
} // namespace ops
} // namespace mindspore