src/runtime/NEON/functions/NEInstanceNormalizationLayer.cpp

/*
 * Copyright (c) 2019-2021 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/NEON/functions/NEInstanceNormalizationLayer.h"

#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/KernelDescriptors.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
#include "src/common/utils/Log.h"
#include "src/core/NEON/kernels/NEInstanceNormalizationLayerKernel.h"

namespace arm_compute
{
NEInstanceNormalizationLayer::~NEInstanceNormalizationLayer() = default;

NEInstanceNormalizationLayer::NEInstanceNormalizationLayer(std::shared_ptr<IMemoryManager> memory_manager)
    : _memory_group(std::move(memory_manager)), _normalization_kernel(), _is_nchw(false), _permute_input(), _permute_output(), _permuted_input(), _permuted_output()
{
}

void NEInstanceNormalizationLayer::configure(ITensor *input, ITensor *output, float gamma, float beta, float epsilon)
{
    ARM_COMPUTE_LOG_PARAMS(input, output, gamma, beta, epsilon);

    const DataLayout data_layout       = input->info()->data_layout();
    const auto       kernel_descriptor = InstanceNormalizationLayerKernelInfo{ gamma, beta, epsilon, true };

    // Configure Kernels
    _is_nchw = data_layout == DataLayout::NCHW;

    _normalization_kernel = std::make_unique<NEInstanceNormalizationLayerKernel>();

    if(!_is_nchw)
    {
        _memory_group.manage(&_permuted_input);
        _memory_group.manage(&_permuted_output);

        // Configure the function to transform the input tensor from NHWC -> NCHW
        _permute_input.configure(input, &_permuted_input, PermutationVector(1U, 2U, 0U));
        _permuted_input.info()->set_data_layout(DataLayout::NCHW);

        _normalization_kernel->configure(&_permuted_input, &_permuted_output, kernel_descriptor);
        _permuted_output.info()->set_data_layout(DataLayout::NCHW);

        _permute_output.configure(&_permuted_output, output != nullptr ? output : input, PermutationVector(2U, 0U, 1U));
        _permuted_input.allocator()->allocate();
        _permuted_output.allocator()->allocate();
    }
    else
    {
        _normalization_kernel->configure(input, output, kernel_descriptor);
    }
}

Status NEInstanceNormalizationLayer::validate(const ITensorInfo *input, const ITensorInfo *output, float gamma, float beta, float epsilon)
{
    return NEInstanceNormalizationLayerKernel::validate(&input->clone()->set_data_layout(DataLayout::NCHW),
                                                        &output->clone()->set_data_layout(DataLayout::NCHW),
                                                        InstanceNormalizationLayerKernelInfo{ gamma, beta, epsilon, true });
}

void NEInstanceNormalizationLayer::run()
{
    MemoryGroupResourceScope scope_mg(_memory_group);

    // Permute input
    if(!_is_nchw)
    {
        _permute_input.run();
    }

    NEScheduler::get().schedule(_normalization_kernel.get(), Window::DimZ);

    // Permute output
    if(!_is_nchw)
    {
        _permute_output.run();
    }
}
} // namespace arm_compute