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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 "internal/op/DepthwiseConv2D.h"
#include "internal/op/NodeVisitor.h"
#include <cassert>
namespace internal
{
namespace tflite
{
namespace op
{
namespace DepthwiseConv2D
{
namespace Explicit
{
void Node::accept(NodeVisitor &&v) const { v.visit(*this); }
} // namespace Explicit
namespace Implicit
{
void Node::accept(NodeVisitor &&v) const { v.visit(*this); }
} // namespace Implicit
} // namespace DepthwiseConv2D
} // namespace op
} // namespace tflite
} // namespace internal
namespace internal
{
namespace tflite
{
namespace op
{
namespace DepthwiseConv2D
{
namespace Explicit
{
Param::Param(uint32_t inputCount, const uint32_t *inputs, uint32_t outputCount,
const uint32_t *outputs)
{
assert(inputCount == 11 && outputCount == 1);
ofm_index = outputs[0];
// Each input should be interpreted as follows:
//
// 0 -> IFM Tensor Index
// 1 -> Kernel Tensor Index
// 2 -> Bias Tensor Index
// 3 -> Padding_left index
// 4 -> Padding_right index
// 5 -> Padding_top index
// 6 -> Padding_bottom index
// 7 -> Stride (width) Index
// 8 -> Stride (height) INdex
// 9 -> Depthwise Multiplier
// 10 -> Activation Index
ifm_index = inputs[0];
ker_index = inputs[1];
bias_index = inputs[2];
padding_left_index = inputs[3];
padding_right_index = inputs[4];
padding_top_index = inputs[5];
padding_bottom_index = inputs[6];
hstride_index = inputs[7];
vstride_index = inputs[8];
multiplier_index = inputs[9];
activation_index = inputs[10];
}
} // namespace Explicit
namespace Implicit
{
Param::Param(uint32_t inputCount, const uint32_t *inputs, uint32_t outputCount,
const uint32_t *outputs)
{
assert(inputCount == 8 && outputCount == 1);
ofm_index = outputs[0];
// Each input should be interpreted as follows:
//
// 0 -> IFM Tensor Index
// 1 -> Kernel Tensor Index
// 2 -> Bias Tensor Index
// 3 -> Padding Code (ANEURALNETWORKS_PADDING_SAME or ANEURALNETWORKS_PADDING_VALID) Index
// 4 -> Stride (width) Index
// 5 -> Stride (height) INdex
// 6 -> Depthwise Multiplier
// 7 -> Activation Index
ifm_index = inputs[0];
ker_index = inputs[1];
bias_index = inputs[2];
padding_index = inputs[3];
hstride_index = inputs[4];
vstride_index = inputs[5];
multiplier_index = inputs[6];
activation_index = inputs[7];
}
} // namespace Implicit
} // namespace DepthwiseConv2D
} // namespace op
} // namespace tflite
} // namespace internal
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