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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 "PoolLayer.h"
#include <cker/operation/AveragePool.h>
#include <cker/operation/MaxPool.h>
#include <unordered_map>
namespace onert
{
namespace backend
{
namespace cpu
{
namespace ops
{
namespace
{
template <typename T>
void avgPool2D(const nnfw::cker::PoolParams ¶ms, const IPortableTensor *input,
IPortableTensor *output)
{
nnfw::cker::AveragePool<T>(params, getShape(input), getBuffer<T>(input), getShape(output),
getBuffer<T>(output));
}
template <typename T>
void maxPool2D(const nnfw::cker::PoolParams ¶ms, const IPortableTensor *input,
IPortableTensor *output)
{
nnfw::cker::MaxPool<T>(params, getShape(input), getBuffer<T>(input), getShape(output),
getBuffer<T>(output));
}
template <typename T>
std::function<void(const IPortableTensor *, IPortableTensor *)>
generateKernelGeneric(const nnfw::cker::PoolParams ¶ms, PoolType op_type)
{
if (op_type == PoolType::kAvg)
{
return std::bind(&avgPool2D<T>, params, std::placeholders::_1, std::placeholders::_2);
}
else if (op_type == PoolType::kMax)
{
return std::bind(&maxPool2D<T>, params, std::placeholders::_1, std::placeholders::_2);
}
else
{
throw std::runtime_error{"Pool: unsupported pool type"};
}
}
} // namespace
PoolLayer::PoolLayer() : _input(nullptr), _output(nullptr), _kernel()
{
// DO NOTHING
}
#define POOLING_PARAMETERS \
nnfw::cker::PoolParams op_params; \
op_params.stride_height = strideHeight; \
op_params.stride_width = strideWidth; \
op_params.filter_height = kernelHeight; \
op_params.filter_width = kernelWidth; \
op_params.padding_values.height = (int8_t)paddingTop; \
op_params.padding_values.width = (int8_t)paddingLeft; \
op_params.float_activation_min = 0; \
op_params.float_activation_max = 0; \
op_params.quantized_activation_min = 0; \
op_params.quantized_activation_max = 0;
void PoolLayer::configure(const IPortableTensor *input, const uint32_t paddingLeft, const uint32_t,
const uint32_t paddingTop, const uint32_t, const uint32_t strideWidth,
const uint32_t strideHeight, const uint32_t kernelWidth,
const uint32_t kernelHeight, const ir::Activation activation,
IPortableTensor *output, const PoolType op_type)
{
assert(input != nullptr);
assert(output != nullptr);
_input = input;
_output = output;
POOLING_PARAMETERS
switch (_input->data_type())
{
case OperandType::FLOAT32:
{
float output_activation_min = 0;
float output_activation_max = 0;
CalculateActivationRange<float>(activation, &output_activation_min, &output_activation_max);
op_params.float_activation_min = output_activation_min;
op_params.float_activation_max = output_activation_max;
_kernel = generateKernelGeneric<float>(op_params, op_type);
break;
}
case OperandType::QUANT_UINT8_ASYMM:
{
int32_t output_activation_min = 0;
int32_t output_activation_max = 0;
CalculateActivationRangeQuantized(activation, _output, &output_activation_min,
&output_activation_max);
op_params.quantized_activation_min = output_activation_min;
op_params.quantized_activation_max = output_activation_max;
_kernel = generateKernelGeneric<uint8_t>(op_params, op_type);
break;
}
case OperandType::QUANT_INT8_ASYMM:
{
int32_t output_activation_min = 0;
int32_t output_activation_max = 0;
CalculateActivationRangeQuantized(activation, _output, &output_activation_min,
&output_activation_max);
op_params.quantized_activation_min = output_activation_min;
op_params.quantized_activation_max = output_activation_max;
_kernel = generateKernelGeneric<int8_t>(op_params, op_type);
break;
}
default:
throw std::runtime_error{"Pool: unsupported data type"};
}
}
void PoolLayer::run() { _kernel(_input, _output); }
#undef AVGPOOLING_PARAMETERS
} // namespace ops
} // namespace cpu
} // namespace backend
} // namespace onert
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