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/*
* Copyright (c) 2018 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 <gtest/gtest.h>
#include "graph/Graph.h"
#include "cpp14/memory.h"
#include "model/operation/Conv2DNode.h"
#include "model/operation/ConcatNode.h"
#include "model/operand/Index.h"
#include "model/operand/IndexSet.h"
#include <stdexcept>
using Index = neurun::model::operand::IO::Index;
using IndexSet = neurun::model::operand::IndexSet;
using GraphNodeInitParam = neurun::model::operation::Node::InitParam;
TEST(graph_operation_setIO, operation_setIO_conv)
{
neurun::graph::Graph graph;
neurun::model::operand::Shape shape{1u};
neurun::model::operand::TypeInfo type{ANEURALNETWORKS_TENSOR_INT32, 0, 0};
shape.dim(0) = 3;
// Add Conv
std::vector<uint32_t> params;
for (int i = 0; i < 7; ++i)
{
params.emplace_back(graph.addOperand(shape, type).asInt());
}
uint32_t outoperand = graph.addOperand(shape, type).asInt();
using GraphNode = neurun::model::operation::Conv2DNode;
auto conv =
nnfw::cpp14::make_unique<GraphNode>(GraphNodeInitParam{7, params.data(), 1, &outoperand});
ASSERT_EQ(conv->getInputs().at(Index{0}).asInt(), params[0]);
conv->setInputs({8, 9, 10});
ASSERT_NE(conv->getInputs().at(Index{0}).asInt(), params[0]);
ASSERT_EQ(conv->getInputs().at(Index{0}).asInt(), 8);
}
TEST(graph_operation_setIO, operation_setIO_concat)
{
neurun::graph::Graph graph;
neurun::model::operand::Shape shape{1u};
neurun::model::operand::TypeInfo type{ANEURALNETWORKS_TENSOR_INT32, 0, 0};
shape.dim(0) = 3;
// Add Concat
std::vector<uint32_t> params;
for (int i = 0; i < 7; ++i)
{
params.emplace_back(graph.addOperand(shape, type).asInt());
}
uint32_t outoperand = graph.addOperand(shape, type).asInt();
using GraphNode = neurun::model::operation::ConcatNode;
auto concat =
nnfw::cpp14::make_unique<GraphNode>(GraphNodeInitParam{7, params.data(), 1, &outoperand});
ASSERT_EQ(concat->getInputs().size(), 6);
ASSERT_EQ(concat->getInputs().at(Index{0}).asInt(), params[0]);
concat->setInputs({80, 6, 9, 11});
ASSERT_EQ(concat->getInputs().size(), 4);
ASSERT_NE(concat->getInputs().at(Index{0}).asInt(), params[0]);
ASSERT_EQ(concat->getInputs().at(Index{0}).asInt(), 80);
ASSERT_EQ(concat->getInputs().at(Index{2}).asInt(), 9);
ASSERT_THROW(concat->getInputs().at(Index{5}), std::out_of_range);
}
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