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Maxence Naud authoredMaxence Naud authored
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PadImpl.cpp 2.71 KiB
/********************************************************************************
* Copyright (c) 2023 CEA-List
*
* This program and the accompanying materials are made available under the
* terms of the Eclipse Public License 2.0 which is available at
* http://www.eclipse.org/legal/epl-2.0.
*
* SPDX-License-Identifier: EPL-2.0
*
********************************************************************************/
#include <cstddef>
#include <vector>
#include "aidge/backend/cpu/data/GetCPUPtr.h"
#include "aidge/backend/cpu/operator/PadImpl.hpp"
#include "aidge/backend/cpu/operator/PadImpl_kernels.hpp"
#include "aidge/operator/Pad.hpp"
#include "aidge/utils/Types.h"
Aidge::Elts_t Aidge::Pad_ProdConso_cpu::getNbRequiredProtected(Aidge::IOIndex_t inputIdx) const {
AIDGE_ASSERT(inputIdx == 0, "input index out of range."
"{} Operator has only one input", mOp.type());
(void) inputIdx;
// Padding cannot be in-place!
// We must ensure that we do not override data that has not been consummed yet.
const auto inputSize = std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->size();
const auto outputSize = std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->size();
return Elts_t::DataElts(outputSize - inputSize);
}
template <>
void Aidge::PadImpl1D_cpu::forward() {
const auto& op_ = dynamic_cast<const Pad_Op<1>&>(mOp);
AIDGE_ASSERT(op_.getInput(0), "missing input #0 in Pad Operator.");
// Find the correct kernel type
const auto impl = Registrar<PadImpl1D_cpu>::create(getBestMatch(getRequiredSpec()));
// Call kernel
impl.forward(op_.beginEndBorders(),
op_.borderType(),
op_.borderValue(),
op_.getInput(0)->template dims<3>(),
getCPUPtr(mOp.getRawInput(0)),
getCPUPtr(mOp.getRawOutput(0)));
}
template <>
void Aidge::PadImpl1D_cpu::backward() {
AIDGE_THROW_OR_ABORT(std::runtime_error, "Backward not yet implemented for Pad_Op<1> on backend cpu");
}
template <>
void Aidge::PadImpl2D_cpu::forward() {
const auto& op_ = dynamic_cast<const Pad_Op<2>&>(mOp);
AIDGE_ASSERT(op_.getInput(0), "missing input #0 in Pad Operator.");
// Find the correct kernel type
const auto impl = Registrar<PadImpl2D_cpu>::create(getBestMatch(getRequiredSpec()));
// Call kernel
impl.forward(op_.beginEndBorders(),
op_.borderType(),
op_.borderValue(),
op_.getInput(0)->template dims<4>(),
getCPUPtr(mOp.getRawInput(0)),
getCPUPtr(mOp.getRawOutput(0)));
}
template <>
void Aidge::PadImpl2D_cpu::backward() {
AIDGE_THROW_OR_ABORT(std::runtime_error, "Backward not yet implemented for Pad_Op<2> on backend cpu");
}