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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
*
* 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 "GenModelTest.h"
#include <memory>
TEST_F(GenModelTest, OneOp_If)
{
// The model looks just like the below pseudocode
//
// function model(x)
// {
// if (x < 0.0)
// return -100.0;
// else
// return 100.0;
// }
CircleGen cgen;
// constant buffers
std::vector<float> comp_data{0.0};
uint32_t comp_buf = cgen.addBuffer(comp_data);
std::vector<float> then_data{-100};
uint32_t then_buf = cgen.addBuffer(then_data);
std::vector<float> else_data{100};
uint32_t else_buf = cgen.addBuffer(else_data);
// primary subgraph
{
int x = cgen.addTensor({{1}, circle::TensorType_FLOAT32});
int comp = cgen.addTensor({{1}, circle::TensorType_FLOAT32, comp_buf});
int cond = cgen.addTensor({{1}, circle::TensorType_BOOL});
cgen.addOperatorLess({{x, comp}, {cond}});
int ret = cgen.addTensor({{1}, circle::TensorType_FLOAT32});
cgen.addOperatorIf({{cond}, {ret}}, 1, 2);
cgen.setInputsAndOutputs({x}, {ret});
}
// then subgraph
{
cgen.nextSubgraph();
int ret = cgen.addTensor({{1}, circle::TensorType_FLOAT32, then_buf});
cgen.setInputsAndOutputs({}, {ret});
}
// else subgraph
{
cgen.nextSubgraph();
int ret = cgen.addTensor({{1}, circle::TensorType_FLOAT32, else_buf});
cgen.setInputsAndOutputs({}, {ret});
}
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->addTestCase({{{-1.0}}, {{-100.0}}});
_context->addTestCase({{{1.0}}, {{100.0}}});
_context->setBackends({"cpu"});
SUCCEED();
}
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