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/*
* Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/KernelDescriptors.h"
#include "src/core/CL/ICLKernel.h"
#include "src/core/helpers/MemoryHelpers.h"
#include "src/runtime/gpu/cl/operators/ClWinogradConv2d.h"
#include "support/Cast.h"
namespace arm_compute
{
struct CLWinogradConvolutionLayer::Impl
{
const ICLTensor *src{ nullptr };
const ICLTensor *weights{ nullptr };
const ICLTensor *biases{ nullptr };
ICLTensor *dst{ nullptr };
std::unique_ptr<opencl::ClWinogradConv2d> op{ nullptr };
ITensorPack run_pack{};
ITensorPack prep_pack{};
MemoryGroup memory_group{};
WorkspaceData<CLTensor> workspace_tensors{};
bool is_prepared{ false };
};
CLWinogradConvolutionLayer::CLWinogradConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager)
: _impl(std::make_unique<Impl>())
{
_impl->memory_group = MemoryGroup(memory_manager);
}
CLWinogradConvolutionLayer::~CLWinogradConvolutionLayer() = default;
void CLWinogradConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info,
bool enable_fast_math)
{
configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, act_info, enable_fast_math);
}
void CLWinogradConvolutionLayer::configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
const PadStrideInfo &conv_info,
const ActivationLayerInfo &act_info, bool enable_fast_math)
{
_impl->src = input;
_impl->weights = weights;
_impl->biases = biases;
_impl->dst = output;
_impl->op = std::make_unique<opencl::ClWinogradConv2d>();
_impl->op->configure(compile_context, input->info(), weights->info(), (biases != nullptr ? biases->info() : nullptr), output->info(), conv_info, act_info, enable_fast_math);
_impl->run_pack =
{
{ TensorType::ACL_SRC_0, _impl->src },
{ TensorType::ACL_SRC_1, _impl->weights },
{ TensorType::ACL_SRC_2, _impl->biases },
{ TensorType::ACL_DST, _impl->dst }
};
_impl->prep_pack = { { TensorType::ACL_SRC_1, _impl->weights } };
_impl->workspace_tensors = manage_workspace<CLTensor>(_impl->op->workspace(), _impl->memory_group, _impl->run_pack, _impl->prep_pack);
}
Status CLWinogradConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
const ActivationLayerInfo &act_info, bool enable_fast_math)
{
return opencl::ClWinogradConv2d::validate(input, weights, biases, output, conv_info, act_info, enable_fast_math);
}
void CLWinogradConvolutionLayer::run()
{
MemoryGroupResourceScope scope_mg(_impl->memory_group);
prepare();
_impl->op->run(_impl->run_pack);
}
void CLWinogradConvolutionLayer::prepare()
{
if(!_impl->is_prepared)
{
_impl->op->prepare(_impl->prep_pack);
_impl->is_prepared = true;
}
}
} // namespace arm_compute
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