Slice.cpp

/********************************************************************************
 * 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 "aidge/operator/Slice.hpp"
#include "aidge/utils/Types.h"
#include "aidge/utils/ErrorHandling.hpp"

#include <cassert>
#include <cstddef>
#include <string>
#include <utility>
#include <vector>

#include "aidge/backend/OperatorImpl.hpp"
#include "aidge/utils/ErrorHandling.hpp"
#include "aidge/utils/Types.h"

void Aidge::Slice_OpImpl::forward() {
    const Slice_Op& op = dynamic_cast<const Slice_Op&>(mOp);
    const auto inputDims = op.getInput(0)->dims();
    auto slicedDims = op.getInput(0)->dims();

    std::size_t beginning = 0;
    DimSize_t nbAxes = op.getAttr<SliceAttr::Axes>().size();
    for (std::size_t i = 0; i < nbAxes; ++i) {
        // For each slice operation get the params and cast them to size_t
        const std::int64_t axis_ = op.getAttr<SliceAttr::Axes>()[i];
        const std::int64_t start_ = op.getAttr<SliceAttr::Starts>()[i];
        const std::int64_t end_ = op.getAttr<SliceAttr::Ends>()[i];
        const std::size_t axis = axis_ >= 0 ? axis_ : static_cast<std::size_t>(axis_) + inputDims.size();
        const std::size_t start = start_ >= 0 ? start_ : start_ + inputDims[axis];
        const std::size_t end = end_ >= 0 ? end_ : end_ + inputDims[axis];
        std::size_t stride = 1;
        for (std::size_t j = inputDims.size() - 1; j > axis; --j) stride *= inputDims[j];
        beginning += start * stride;
        const std::size_t sliceLength = end - start + 1;
        slicedDims[axis] = sliceLength;
    }

    const std::size_t nbDims = slicedDims.size();

    // for inputDims = {4,5,5,3} & slicedDims = {3,2,2,1}, substractDims = {1,5,5,3}
    std::vector<std::size_t> substractedDims = std::vector<std::size_t>(nbDims);
    for (std::size_t i = 0; i < nbDims; ++i) {
        substractedDims[i] = inputDims[i] - slicedDims[i];
    }

    // for slicedDims = {3,2,2,1}, prodSlicedDims = {12,4,2,1}
    std::vector<std::size_t> prodSlicedDims = std::vector<std::size_t>(nbDims);
    std::vector<std::size_t> prodInputDims = std::vector<std::size_t>(nbDims + 1);
    prodSlicedDims[nbDims - 1] = slicedDims[nbDims - 1];
    prodInputDims[nbDims - 1] = inputDims[nbDims - 1];
    prodInputDims[nbDims] = 1;
    for (std::size_t i = 2; i <= nbDims; ++i) {
        prodSlicedDims[nbDims - i] = prodSlicedDims[nbDims - i + 1] * slicedDims[nbDims - i];
        prodInputDims[nbDims - i] = prodInputDims[nbDims - i + 1] * inputDims[nbDims - i];
    }

    std::size_t i = beginning;
    std::size_t size = 0;
    std::size_t offset = 0;
    for (std::size_t j = 0; j < prodSlicedDims[0];) {
        ++size;
        ++i;
        ++j;
        bool newChunk = false;
        for (std::size_t idx = nbDims - 1; idx > 0; --idx) {
            if (j % prodSlicedDims[idx] == 0) {
                i += substractedDims[idx] * prodInputDims[idx + 1];
                newChunk = true;
            }
        }

        if (newChunk) {
            op.getOutput(0)->getImpl()->copy(op.getInput(0)->getImpl()->rawPtr(beginning), size, offset);
            beginning = i;
            offset += size;
            size = 0;
        }
    }

    if (size > 0) {
        op.getOutput(0)->getImpl()->copy(op.getInput(0)->getImpl()->rawPtr(beginning), size, offset);
    }
}

const std::string Aidge::Slice_Op::Type = "Slice";

bool Aidge::Slice_Op::forwardDims(bool /*allowDataDependency*/) {
    // check input have been associated
    if (!getInput(0) || (getInput(0)->empty())) {
        AIDGE_THROW_OR_ABORT(std::runtime_error, "{}: input #0 should be associated with a Tensor", type());
    }

    const DimSize_t nbAxes = this->template getAttr<SliceAttr::Axes>().size();
    std::vector<DimSize_t> outDims = getInput(0)->dims();
    for (std::size_t i = 0; i < nbAxes; ++i) {
        // For each slice operation get the params and cast them to size_t
        const std::int64_t axis_ = this->template getAttr<SliceAttr::Axes>()[i];
        const std::int64_t start_ = this->template getAttr<SliceAttr::Starts>()[i];
        const std::int64_t end_ = this->template getAttr<SliceAttr::Ends>()[i];
        const std::size_t axis = axis_ >= 0 ? static_cast<std::size_t>(axis_) : static_cast<std::size_t>(axis_) + getInput(0)->nbDims();
        const std::size_t start = start_ >= 0 ? static_cast<std::size_t>(start_) : static_cast<std::size_t>(start_) + getInput(0)->dims()[axis];
        const std::size_t end = end_ >= 0 ? static_cast<std::size_t>(end_) : static_cast<std::size_t>(end_) + getInput(0)->dims()[axis];

        const std::size_t sliceLength = end - start + 1;
        // Check if slice length is valid
        if (sliceLength > getInput(0)->dims()[axis])
        {
            AIDGE_THROW_OR_ABORT(std::runtime_error, "ROI of Slice operator out of bounds");
        }
        outDims[axis] = sliceLength;
    }
    mOutputs[0]->resize(outDims);
    return true;
}

void Aidge::Slice_Op::setBackend(const std::string& name, Aidge::DeviceIdx_t device) {
    if (Registrar<Slice_Op>::exists({name})){
        SET_IMPL_MACRO(Slice_Op, *this, name);
    }
    else {
        mImpl = std::make_shared<Slice_OpImpl>(*this);
    }
    mOutputs[0]->setBackend(name, device);
}