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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 "ConcatNode.h"
#include <cassert>
#include "NodeVisitor.h"
namespace neurun
{
namespace model
{
namespace operation
{
void ConcatNode::accept(NodeVisitor &&v) const { v.visit(*this); }
ConcatNode::ConcatNode(const model::operation::Node::InitParam &init_param)
: model::operation::Node{OperandConstraint::createAtLeast(2u)}
{
assert(init_param.input_count >= 2); // At least one one input tensor and axis
assert(init_param.output_count == 1);
// When there are N + 1 inputs, each input should be interpreted as follows:
//
// [0, N) -> Input tensors
// N -> Axis
//
{
operand::IndexSet inds;
for (uint32_t n = 0; n < init_param.input_count - 1; ++n)
{
inds.append(operand::Index{init_param.inputs[n]});
}
setInputs(inds);
}
setOutputs({init_param.outputs[0]});
_param.axis_index = operand::Index{init_param.inputs[init_param.input_count - 1]};
}
} // namespace operation
} // namespace model
} // namespace neurun
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