/*
 * Copyright (c) 2017-2023 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/NEON/functions/NEFullyConnectedLayer.h"

#include "arm_compute/core/ITensorPack.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include "arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h"

#include "src/common/utils/Log.h"
#include "src/core/helpers/MemoryHelpers.h"
#include "src/cpu/operators/CpuFullyConnected.h"

namespace arm_compute
{
using namespace arm_compute::experimental;

struct NEFullyConnectedLayer::Impl
{
    MemoryGroup      memory_group{};
    IWeightsManager *weights_manager{nullptr};

    std::unique_ptr<cpu::CpuFullyConnected> op{nullptr};

    const ITensor *original_weights{nullptr};

    ITensorPack                      run_pack{};
    WorkspaceData<Tensor>            workspace{};
    experimental::MemoryRequirements aux_mem_req{};

    bool is_prepared{false};
    bool dynamic_weights{false};
};

NEFullyConnectedLayer::~NEFullyConnectedLayer() = default;

NEFullyConnectedLayer::NEFullyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager,
                                             IWeightsManager                *weights_manager)
    : _impl(std::make_unique<Impl>())
{
    _impl->memory_group    = MemoryGroup(std::move(memory_manager));
    _impl->weights_manager = weights_manager;
}

void NEFullyConnectedLayer::configure(const ITensor          *input,
                                      const ITensor          *weights,
                                      const ITensor          *biases,
                                      ITensor                *output,
                                      FullyConnectedLayerInfo fc_info,
                                      const WeightsInfo      &weights_info)
{
    // Perform validate step
    ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
    ARM_COMPUTE_ERROR_THROW_ON(NEFullyConnectedLayer::validate(input->info(), weights->info(),
                                                               biases != nullptr ? biases->info() : nullptr,
                                                               output->info(), fc_info, weights_info));
    ARM_COMPUTE_LOG_PARAMS(input, weights, biases, output, fc_info);

    _impl->op               = std::make_unique<cpu::CpuFullyConnected>();
    _impl->original_weights = weights;
    _impl->is_prepared      = false;

    _impl->op->configure(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(),
                         fc_info, weights_info);

    if (_impl->weights_manager != nullptr)
    {
        _impl->weights_manager->manage(_impl->original_weights);
    }

    _impl->aux_mem_req = _impl->op->workspace();
    _impl->run_pack    = {{ACL_SRC_0, input}, {ACL_SRC_1, weights}, {ACL_SRC_2, biases}, {ACL_DST, output}};
    _impl->workspace =
        manage_workspace<Tensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->run_pack);

    _impl->dynamic_weights = !weights->info()->are_values_constant() && fc_info.transpose_weights &&
                             !fc_info.are_weights_reshaped && !fc_info.retain_internal_weights;
}

Status NEFullyConnectedLayer::has_opt_impl(arm_compute::WeightFormat     &expected_weight_format,
                                           const ITensorInfo             *input,
                                           const ITensorInfo             *weights,
                                           const ITensorInfo             *biases,
                                           const ITensorInfo             *output,
                                           const FullyConnectedLayerInfo &fc_info,
                                           const WeightsInfo             &weights_info)
{
    return cpu::CpuFullyConnected::has_opt_impl(expected_weight_format, input, weights, biases, output, fc_info,
                                                weights_info);
}

Status NEFullyConnectedLayer::validate(const ITensorInfo      *input,
                                       const ITensorInfo      *weights,
                                       const ITensorInfo      *biases,
                                       const ITensorInfo      *output,
                                       FullyConnectedLayerInfo fc_info,
                                       const WeightsInfo      &weights_info)
{
    return cpu::CpuFullyConnected::validate(input, weights, biases, output, fc_info, weights_info);
}

void NEFullyConnectedLayer::run()
{
    if (!_impl->dynamic_weights)
    {
        prepare();
    }

    MemoryGroupResourceScope scope_mg(_impl->memory_group);
    _impl->op->run(_impl->run_pack);
}

void NEFullyConnectedLayer::prepare()
{
    if (!_impl->is_prepared)
    {
        _impl->op->prepare(_impl->run_pack);

        // Release temporary tensors that are only used in prepare stage
        release_temporaries<Tensor>(_impl->aux_mem_req, _impl->workspace);
        _impl->is_prepared = true;

        // Handle weights managed infrastructure
        if (_impl->weights_manager != nullptr && _impl->weights_manager->are_weights_managed(_impl->original_weights))
        {
            // Ensure that b gets marked as unused (memory released) only after the last function which uses b also finishes its prepare
            // This is for cases where multiple functions share the same b (weights)
            // Therefore when a function marks original b as unused, we pre-mark it in weights manager, and mark it back to used so that it doesn't get released before its last reference
            const ITensor *original_b = _impl->original_weights;
            if (!original_b->is_used())
            {
                _impl->weights_manager->pre_mark_as_unused(original_b);
            }
            _impl->original_weights->mark_as_used();
            _impl->weights_manager->release(_impl->original_weights);
        }
    }
}
} // namespace arm_compute