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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 "ReduceLayer.h"
#include "OperationUtils.h"
#include <cker/operation/Reduce.h>
namespace onert
{
namespace backend
{
namespace cpu
{
namespace ops
{
namespace
{
template <typename T>
void evalLogic(const IPortableTensor *input, IPortableTensor *output, const std::vector<int> &axes,
bool keep_dims, T init_value, nnfw::cker::Reduce &reduce_kernel,
T reducer(const T current, const T in))
{
reduce_kernel.prepare(input->num_dimensions(), axes.size());
bool result = reduce_kernel.ReduceGeneric<T>(
getTensorShape(input), reinterpret_cast<const T *>(input->buffer()), getTensorShape(output),
reinterpret_cast<T *>(output->buffer()), axes, keep_dims, init_value, reducer);
if (!result)
{
throw std::runtime_error{"Reduce: Fail to run"};
}
}
template <typename T>
void evalType(const IPortableTensor *input, IPortableTensor *output, const std::vector<int> &axes,
bool keep_dims, nnfw::cker::Reduce &reduce_kernel, ReduceType reduce_type)
{
switch (reduce_type)
{
case ReduceType::kSum:
return evalLogic<T>(input, output, axes, keep_dims, static_cast<T>(0), reduce_kernel,
[](const T current, const T in) -> T { return in + current; });
break;
case ReduceType::kProd:
return evalLogic<T>(input, output, axes, keep_dims, static_cast<T>(1), reduce_kernel,
[](const T current, const T in) -> T { return in * current; });
break;
case ReduceType::kMax:
return evalLogic<T>(
input, output, axes, keep_dims, std::numeric_limits<T>::lowest(), reduce_kernel,
[](const T current, const T in) -> T { return (in > current) ? in : current; });
break;
case ReduceType::kMin:
return evalLogic<T>(
input, output, axes, keep_dims, std::numeric_limits<T>::max(), reduce_kernel,
[](const T current, const T in) -> T { return (in < current) ? in : current; });
break;
default:
throw std::runtime_error{"Reduce: Unsupported reduce type"};
}
}
// Template specialization for bool type
template <>
void evalType<bool>(const IPortableTensor *input, IPortableTensor *output,
const std::vector<int> &axes, bool keep_dims, nnfw::cker::Reduce &reduce_kernel,
ReduceType reduce_type)
{
switch (reduce_type)
{
case ReduceType::kAny:
return evalLogic<bool>(
input, output, axes, keep_dims, false, reduce_kernel,
[](const bool current, const bool in) -> bool { return in || current; });
break;
case ReduceType::kAll:
return evalLogic<bool>(
input, output, axes, keep_dims, true, reduce_kernel,
[](const bool current, const bool in) -> bool { return in && current; });
break;
default:
throw std::runtime_error{"Reduce: Unsupported reduce type"};
}
}
template <ReduceType reduce_type>
void evalGeneric(const IPortableTensor *input, IPortableTensor *output,
const std::vector<int> &axes, bool keep_dims, nnfw::cker::Reduce &reduce_kernel)
{
switch (input->data_type())
{
case OperandType::FLOAT32:
return evalType<float>(input, output, axes, keep_dims, reduce_kernel, reduce_type);
case OperandType::INT32:
return evalType<int32_t>(input, output, axes, keep_dims, reduce_kernel, reduce_type);
case OperandType::BOOL8:
return evalType<bool>(input, output, axes, keep_dims, reduce_kernel, reduce_type);
default:
throw std::runtime_error{"Reduce(generic): unsupported data type"};
}
}
} // namespace
ReduceLayer::ReduceLayer()
: _input(nullptr), _axes(nullptr), _output(nullptr), _reduceType(ReduceType::kAny),
_keep_dims(false), _reduce_kernel(new nnfw::cker::Reduce())
{
// DO NOTHING
}
ReduceLayer::~ReduceLayer() = default;
void ReduceLayer::configure(const IPortableTensor *input, const IPortableTensor *axes,
IPortableTensor *output, ReduceType reduceType, bool keep_dims)
{
_input = input;
_axes = axes;
_output = output;
_reduceType = reduceType;
_keep_dims = keep_dims;
}
void ReduceLayer::run()
{
const auto axes = getReducerAxes(_axes);
switch (_reduceType)
{
case ReduceType::kSum:
evalGeneric<ReduceType::kSum>(_input, _output, axes, _keep_dims, *_reduce_kernel);
break;
case ReduceType::kProd:
evalGeneric<ReduceType::kProd>(_input, _output, axes, _keep_dims, *_reduce_kernel);
break;
case ReduceType::kMax:
evalGeneric<ReduceType::kMax>(_input, _output, axes, _keep_dims, *_reduce_kernel);
break;
case ReduceType::kMin:
evalGeneric<ReduceType::kMin>(_input, _output, axes, _keep_dims, *_reduce_kernel);
break;
case ReduceType::kAny:
evalGeneric<ReduceType::kAny>(_input, _output, axes, _keep_dims, *_reduce_kernel);
break;
case ReduceType::kAll:
evalGeneric<ReduceType::kAll>(_input, _output, axes, _keep_dims, *_reduce_kernel);
break;
default:
throw std::runtime_error{"ReduceSum: Unsupported reduce type"};
}
}
} // namespace ops
} // namespace cpu
} // namespace backend
} // namespace onert
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