/*
 * 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 "internal/op/FullyConnected.h"
#include "internal/op/NodeVisitor.h"

#include <cassert>

namespace internal
{
namespace tflite
{
namespace op
{
namespace FullyConnected
{

void Node::accept(NodeVisitor &&v) const { v.visit(*this); }

} // namespace FullyConnected
} // namespace op
} // namespace tflite
} // namespace internal

namespace internal
{
namespace tflite
{
namespace op
{
namespace FullyConnected
{

Param::Param(uint32_t inputCount, const uint32_t *inputs, uint32_t outputCount,
             const uint32_t *outputs)
{
  assert(inputCount == 4 && outputCount == 1);

  output_index = outputs[0];

  // Each input should be interpreted as follows:
  //
  //  0 -> A tensor, specifying the input.
  //  1 -> A 2-D tensor, specifying the weights
  //  2 -> A 1-D tensor, specifying the bias
  //  3 -> An INT32 value, and has to be one of the FuseCode values
  input_index = inputs[0];
  weight_index = inputs[1];
  bias_index = inputs[2];
  activation_index = inputs[3];
}

} // namespace FullyConnected
} // namespace op
} // namespace tflite
} // namespace internal