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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_Add_VarToConst)
{
CircleGen cgen;
std::vector<float> rhs_data{5, 4, 7, 4};
uint32_t rhs_buf = cgen.addBuffer(rhs_data);
int lhs = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
int rhs = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32, rhs_buf});
int out = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorAdd({{lhs, rhs}, {out}}, circle::ActivationFunctionType_NONE);
cgen.setInputsAndOutputs({lhs}, {out});
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->addTestCase({{{1, 3, 2, 4}}, {{6, 7, 9, 8}}});
_context->addTestCase({{{0, 1, 2, 3}}, {{5, 5, 9, 7}}});
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
SUCCEED();
}
TEST_F(GenModelTest, OneOp_Add_VarToVar)
{
CircleGen cgen;
int lhs = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
int rhs = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
int out = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorAdd({{lhs, rhs}, {out}}, circle::ActivationFunctionType_NONE);
cgen.setInputsAndOutputs({lhs, rhs}, {out});
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->addTestCase({{{1, 3, 2, 4}, {5, 4, 7, 4}}, {{6, 7, 9, 8}}});
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
SUCCEED();
}
TEST_F(GenModelTest, neg_OneOp_Add_InvalidShape)
{
CircleGen cgen;
int lhs = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
int rhs = cgen.addTensor({{1, 2, 3, 1}, circle::TensorType::TensorType_FLOAT32});
int out = cgen.addTensor({{1, 2, 3, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorAdd({{lhs, rhs}, {out}}, circle::ActivationFunctionType_NONE);
cgen.setInputsAndOutputs({lhs, rhs}, {out});
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
_context->setCompileFail();
SUCCEED();
}
TEST_F(GenModelTest, neg_OneOp_Add_InvalidShapeConst)
{
CircleGen cgen;
std::vector<float> rhs_data{5, 4, 0, 7, 4, 0};
uint32_t rhs_buf = cgen.addBuffer(rhs_data);
int lhs = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
int rhs = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32, rhs_buf});
int out = cgen.addTensor({{1, 2, 3, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorAdd({{lhs, rhs}, {out}}, circle::ActivationFunctionType_NONE);
cgen.setInputsAndOutputs({lhs, rhs}, {out});
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
_context->setCompileFail();
SUCCEED();
}
TEST_F(GenModelTest, neg_OneOp_Add_OneOperand)
{
CircleGen cgen;
int in = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
int out = cgen.addTensor({{1, 2, 3, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorAdd({{in}, {out}}, circle::ActivationFunctionType_NONE);
cgen.setInputsAndOutputs({in}, {out});
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
_context->setCompileFail();
SUCCEED();
}
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