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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"
TEST_F(GenModelTest, OneOp_Pad)
{
CircleGen cgen;
int in = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
std::vector<int32_t> padding_data{0, 0, 1, 1, 1, 1, 0, 0};
uint32_t padding_buf = cgen.addBuffer(padding_data);
int padding = cgen.addTensor({{4, 2}, circle::TensorType::TensorType_INT32, padding_buf});
int out = cgen.addTensor({{1, 4, 4, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorPad({{in, padding}, {out}});
cgen.setInputsAndOutputs({in}, {out});
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->addTestCase({{{1, 2, 3, 4}}, {{0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4, 0, 0, 0, 0, 0}}});
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
SUCCEED();
}
TEST_F(GenModelTest, neg_OneOp_Pad_InvalidPadRank)
{
CircleGen cgen;
int in = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
std::vector<int32_t> padding_data{1, 1, 1, 1};
uint32_t padding_buf = cgen.addBuffer(padding_data);
int padding = cgen.addTensor({{4}, circle::TensorType::TensorType_INT32, padding_buf});
int out = cgen.addTensor({{1, 4, 4, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorPad({{in, padding}, {out}});
cgen.setInputsAndOutputs({in}, {out});
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
_context->setCompileFail();
SUCCEED();
}
TEST_F(GenModelTest, neg_OneOp_Pad_InvalidPadDim0)
{
CircleGen cgen;
int in = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
std::vector<int32_t> padding_data{1, 1, 1, 1};
uint32_t padding_buf = cgen.addBuffer(padding_data);
int padding = cgen.addTensor({{2, 2}, circle::TensorType::TensorType_INT32, padding_buf});
int out = cgen.addTensor({{1, 4, 4, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorPad({{in, padding}, {out}});
cgen.setInputsAndOutputs({in}, {out});
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
_context->setCompileFail();
SUCCEED();
}
TEST_F(GenModelTest, neg_OneOp_Pad_InvalidPadDim1)
{
CircleGen cgen;
int in = cgen.addTensor({{1, 1, 1, 1}, circle::TensorType::TensorType_FLOAT32});
std::vector<int32_t> padding_data{1, 1, 1, 1};
uint32_t padding_buf = cgen.addBuffer(padding_data);
int padding = cgen.addTensor({{4, 1}, circle::TensorType::TensorType_INT32, padding_buf});
int out = cgen.addTensor({{2, 2, 2, 2}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorPad({{in, padding}, {out}});
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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